예제 #1
0
def main():
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

    cl_ctx = cl.create_some_context()
    queue = cl.CommandQueue(cl_ctx)

    from meshmode.mesh.generation import generate_torus

    rout = 10
    rin = 1
    if 1:
        base_mesh = generate_torus(
                rout, rin, 40, 4,
                mesh_order)

        from meshmode.mesh.processing import affine_map, merge_disjoint_meshes
        # nx = 1
        # ny = 1
        nz = 1
        dz = 0
        meshes = [
                affine_map(
                    base_mesh,
                    A=np.diag([1, 1, 1]),
                    b=np.array([0, 0, iz*dz]))
                for iz in range(nz)]

        mesh = merge_disjoint_meshes(meshes, single_group=True)

        if 0:
            from meshmode.mesh.visualization import draw_curve
            draw_curve(mesh)
            import matplotlib.pyplot as plt
            plt.show()

    pre_density_discr = Discretization(
            cl_ctx, mesh,
            InterpolatoryQuadratureSimplexGroupFactory(bdry_quad_order))

    from pytential.qbx import (
            QBXLayerPotentialSource, QBXTargetAssociationFailedException)
    qbx, _ = QBXLayerPotentialSource(
            pre_density_discr, fine_order=bdry_ovsmp_quad_order, qbx_order=qbx_order,
            fmm_order=fmm_order
            ).with_refinement()
    density_discr = qbx.density_discr

    # {{{ describe bvp

    from sumpy.kernel import LaplaceKernel
    kernel = LaplaceKernel(3)

    cse = sym.cse

    sigma_sym = sym.var("sigma")
    #sqrt_w = sym.sqrt_jac_q_weight(3)
    sqrt_w = 1
    inv_sqrt_w_sigma = cse(sigma_sym/sqrt_w)

    # -1 for interior Dirichlet
    # +1 for exterior Dirichlet
    loc_sign = +1

    bdry_op_sym = (loc_sign*0.5*sigma_sym
            + sqrt_w*(
                sym.S(kernel, inv_sqrt_w_sigma)
                + sym.D(kernel, inv_sqrt_w_sigma)
                ))

    # }}}

    bound_op = bind(qbx, bdry_op_sym)

    # {{{ fix rhs and solve

    nodes = density_discr.nodes().with_queue(queue)
    source = np.array([rout, 0, 0])

    def u_incoming_func(x):
        #        return 1/cl.clmath.sqrt( (x[0] - source[0])**2
        #                                +(x[1] - source[1])**2
        #                                +(x[2] - source[2])**2 )
        return 1.0/la.norm(x.get()-source[:, None], axis=0)

    bc = cl.array.to_device(queue, u_incoming_func(nodes))

    bvp_rhs = bind(qbx, sqrt_w*sym.var("bc"))(queue, bc=bc)

    from pytential.solve import gmres
    gmres_result = gmres(
            bound_op.scipy_op(queue, "sigma", dtype=np.float64),
            bvp_rhs, tol=1e-14, progress=True,
            stall_iterations=0,
            hard_failure=True)

    sigma = bind(qbx, sym.var("sigma")/sqrt_w)(queue, sigma=gmres_result.solution)

    # }}}

    from meshmode.discretization.visualization import make_visualizer
    bdry_vis = make_visualizer(queue, density_discr, 20)
    bdry_vis.write_vtk_file("laplace.vtu", [
        ("sigma", sigma),
        ])

    # {{{ postprocess/visualize

    repr_kwargs = dict(qbx_forced_limit=None)
    representation_sym = (
            sym.S(kernel, inv_sqrt_w_sigma, **repr_kwargs)
            + sym.D(kernel, inv_sqrt_w_sigma, **repr_kwargs))

    from sumpy.visualization import FieldPlotter
    fplot = FieldPlotter(np.zeros(3), extent=20, npoints=50)

    targets = cl.array.to_device(queue, fplot.points)

    qbx_stick_out = qbx.copy(target_stick_out_factor=0.2)

    try:
        fld_in_vol = bind(
                (qbx_stick_out, PointsTarget(targets)),
                representation_sym)(queue, sigma=sigma).get()
    except QBXTargetAssociationFailedException as e:
        fplot.write_vtk_file(
                "failed-targets.vts",
                [
                    ("failed", e.failed_target_flags.get(queue))
                    ]
                )
        raise

    #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
    fplot.write_vtk_file(
            "potential-laplace-3d.vts",
            [
                ("potential", fld_in_vol),
                ]
            )
def test_target_specific_qbx(ctx_getter, op, helmholtz_k, qbx_order):
    logging.basicConfig(level=logging.INFO)

    cl_ctx = ctx_getter()
    queue = cl.CommandQueue(cl_ctx)

    target_order = 4
    fmm_tol = 1e-3

    from meshmode.mesh.generation import generate_icosphere
    mesh = generate_icosphere(1, target_order)

    from meshmode.discretization import Discretization
    from meshmode.discretization.poly_element import \
        InterpolatoryQuadratureSimplexGroupFactory
    from pytential.qbx import QBXLayerPotentialSource
    pre_density_discr = Discretization(
        cl_ctx, mesh, InterpolatoryQuadratureSimplexGroupFactory(target_order))

    from sumpy.expansion.level_to_order import SimpleExpansionOrderFinder

    refiner_extra_kwargs = {}

    if helmholtz_k != 0:
        refiner_extra_kwargs["kernel_length_scale"] = 5 / abs(helmholtz_k)

    qbx, _ = QBXLayerPotentialSource(
        pre_density_discr,
        4 * target_order,
        qbx_order=qbx_order,
        fmm_level_to_order=SimpleExpansionOrderFinder(fmm_tol),
        fmm_backend="fmmlib",
        _expansions_in_tree_have_extent=True,
        _expansion_stick_out_factor=0.9,
        _use_target_specific_qbx=False,
    ).with_refinement(**refiner_extra_kwargs)

    density_discr = qbx.density_discr

    nodes = density_discr.nodes().with_queue(queue)
    u_dev = clmath.sin(nodes[0])

    if helmholtz_k == 0:
        kernel = LaplaceKernel(3)
        kernel_kwargs = {}
    else:
        kernel = HelmholtzKernel(3, allow_evanescent=True)
        kernel_kwargs = {"k": sym.var("k")}

    u_sym = sym.var("u")

    if op == "S":
        op = sym.S
    elif op == "D":
        op = sym.D
    elif op == "Sp":
        op = sym.Sp
    else:
        raise ValueError("unknown operator: '%s'" % op)

    expr = op(kernel, u_sym, qbx_forced_limit=-1, **kernel_kwargs)

    bound_op = bind(qbx, expr)
    pot_ref = bound_op(queue, u=u_dev, k=helmholtz_k).get()

    qbx = qbx.copy(_use_target_specific_qbx=True)
    bound_op = bind(qbx, expr)
    pot_tsqbx = bound_op(queue, u=u_dev, k=helmholtz_k).get()

    assert np.allclose(pot_tsqbx, pot_ref, atol=1e-13, rtol=1e-13)
예제 #3
0
def timing_run(nx, ny, visualize=False):
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

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

    mesh = make_mesh(nx=nx, ny=ny, visualize=visualize)

    density_discr = Discretization(
        actx, mesh,
        InterpolatoryQuadratureSimplexGroupFactory(bdry_quad_order))

    from pytential.qbx import (QBXLayerPotentialSource,
                               QBXTargetAssociationFailedException)
    qbx = QBXLayerPotentialSource(density_discr,
                                  fine_order=bdry_ovsmp_quad_order,
                                  qbx_order=qbx_order,
                                  fmm_order=fmm_order)

    places = {"qbx": qbx}
    if visualize:
        from sumpy.visualization import FieldPlotter
        fplot = FieldPlotter(np.zeros(2), extent=5, npoints=1500)
        targets = PointsTarget(actx.from_numpy(fplot.points))

        places.update({
            "plot-targets":
            targets,
            "qbx-indicator":
            qbx.copy(target_association_tolerance=0.05,
                     fmm_level_to_order=lambda lev: 7,
                     qbx_order=2),
            "qbx-target-assoc":
            qbx.copy(target_association_tolerance=0.1)
        })

    from pytential import GeometryCollection
    places = GeometryCollection(places, auto_where="qbx")
    density_discr = places.get_discretization("qbx")

    # {{{ describe bvp

    from sumpy.kernel import HelmholtzKernel
    kernel = HelmholtzKernel(2)

    sigma_sym = sym.var("sigma")
    sqrt_w = sym.sqrt_jac_q_weight(2)
    inv_sqrt_w_sigma = sym.cse(sigma_sym / sqrt_w)

    # Brakhage-Werner parameter
    alpha = 1j

    # -1 for interior Dirichlet
    # +1 for exterior Dirichlet
    loc_sign = +1

    k_sym = sym.var("k")
    S_sym = sym.S(kernel, inv_sqrt_w_sigma, k=k_sym, qbx_forced_limit=+1)
    D_sym = sym.D(kernel, inv_sqrt_w_sigma, k=k_sym, qbx_forced_limit="avg")
    bdry_op_sym = -loc_sign * 0.5 * sigma_sym + sqrt_w * (alpha * S_sym +
                                                          D_sym)

    # }}}

    bound_op = bind(places, bdry_op_sym)

    # {{{ fix rhs and solve

    mode_nr = 3

    from meshmode.dof_array import thaw
    nodes = thaw(actx, density_discr.nodes())
    angle = actx.np.arctan2(nodes[1], nodes[0])

    sigma = actx.np.cos(mode_nr * angle)

    # }}}

    # {{{ postprocess/visualize

    repr_kwargs = dict(k=sym.var("k"), qbx_forced_limit=+1)

    sym_op = sym.S(kernel, sym.var("sigma"), **repr_kwargs)
    bound_op = bind(places, sym_op)

    print("FMM WARM-UP RUN 1: %5d elements" % mesh.nelements)
    bound_op(actx, sigma=sigma, k=k)
    queue.finish()

    print("FMM WARM-UP RUN 2: %5d elements" % mesh.nelements)
    bound_op(actx, sigma=sigma, k=k)
    queue.finish()

    from time import time
    t_start = time()
    bound_op(actx, sigma=sigma, k=k)
    actx.queue.finish()
    elapsed = time() - t_start

    print("FMM TIMING RUN:    %5d elements -> %g s" %
          (mesh.nelements, elapsed))

    if visualize:
        ones_density = density_discr.zeros(queue)
        ones_density.fill(1)
        indicator = bind(places,
                         sym_op,
                         auto_where=("qbx-indicator", "plot-targets"))(
                             queue, sigma=ones_density).get()

        try:
            fld_in_vol = bind(places,
                              sym_op,
                              auto_where=("qbx-target-assoc",
                                          "plot-targets"))(queue,
                                                           sigma=sigma,
                                                           k=k).get()
        except QBXTargetAssociationFailedException as e:
            fplot.write_vtk_file("scaling-study-failed-targets.vts", [
                ("failed", e.failed_target_flags.get(queue)),
            ])
            raise

        fplot.write_vtk_file("scaling-study-potential.vts", [
            ("potential", fld_in_vol),
            ("indicator", indicator),
        ])

    return (mesh.nelements, elapsed)
예제 #4
0
def main():
    # cl.array.to_device(queue, numpy_array)
    from meshmode.mesh.io import generate_gmsh, FileSource
    mesh = generate_gmsh(
        FileSource("ellipsoid.step"),
        2,
        order=2,
        other_options=["-string",
                       "Mesh.CharacteristicLengthMax = %g;" % h])

    from meshmode.mesh.processing import perform_flips
    # Flip elements--gmsh generates inside-out geometry.
    mesh = perform_flips(mesh, np.ones(mesh.nelements))

    print("%d elements" % mesh.nelements)

    from meshmode.mesh.processing import find_bounding_box
    bbox_min, bbox_max = find_bounding_box(mesh)
    bbox_center = 0.5 * (bbox_min + bbox_max)
    bbox_size = max(bbox_max - bbox_min) / 2

    logger.info("%d elements" % mesh.nelements)

    from pytential.qbx import QBXLayerPotentialSource
    from meshmode.discretization import Discretization
    from meshmode.discretization.poly_element import \
            InterpolatoryQuadratureSimplexGroupFactory

    density_discr = Discretization(
        cl_ctx, mesh, InterpolatoryQuadratureSimplexGroupFactory(target_order))

    qbx = QBXLayerPotentialSource(density_discr,
                                  4 * target_order,
                                  qbx_order,
                                  fmm_order=qbx_order + 10,
                                  fmm_backend="fmmlib")

    from pytential.symbolic.pde.maxwell import MuellerAugmentedMFIEOperator
    pde_op = MuellerAugmentedMFIEOperator(
        omega=0.4,
        epss=[1.4, 1.0],
        mus=[1.2, 1.0],
    )
    from pytential import bind, sym

    unk = pde_op.make_unknown("sigma")
    sym_operator = pde_op.operator(unk)
    sym_rhs = pde_op.rhs(sym.make_sym_vector("Einc", 3),
                         sym.make_sym_vector("Hinc", 3))
    sym_repr = pde_op.representation(0, unk)

    if 1:
        expr = sym_repr
        print(sym.pretty(expr))

        print("#" * 80)
        from pytential.target import PointsTarget

        tgt_points = np.zeros((3, 1))
        tgt_points[0, 0] = 100
        tgt_points[1, 0] = -200
        tgt_points[2, 0] = 300

        bound_op = bind((qbx, PointsTarget(tgt_points)), expr)
        print(bound_op.code)

    if 1:

        def green3e(x, y, z, source, strength, k):
            # electric field corresponding to dyadic green's function
            # due to monochromatic electric dipole located at "source".
            # "strength" is the the intensity of the dipole.
            #  E = (I + Hess)(exp(ikr)/r) dot (strength)
            #
            dx = x - source[0]
            dy = y - source[1]
            dz = z - source[2]
            rr = np.sqrt(dx**2 + dy**2 + dz**2)

            fout = np.exp(1j * k * rr) / rr
            evec = fout * strength
            qmat = np.zeros((3, 3), dtype=np.complex128)

            qmat[0, 0] = (2 * dx**2 - dy**2 - dz**2) * (1 - 1j * k * rr)
            qmat[1, 1] = (2 * dy**2 - dz**2 - dx**2) * (1 - 1j * k * rr)
            qmat[2, 2] = (2 * dz**2 - dx**2 - dy**2) * (1 - 1j * k * rr)

            qmat[0, 0] = qmat[0, 0] + (-k**2 * dx**2 * rr**2)
            qmat[1, 1] = qmat[1, 1] + (-k**2 * dy**2 * rr**2)
            qmat[2, 2] = qmat[2, 2] + (-k**2 * dz**2 * rr**2)

            qmat[0, 1] = (3 - k**2 * rr**2 - 3 * 1j * k * rr) * (dx * dy)
            qmat[1, 2] = (3 - k**2 * rr**2 - 3 * 1j * k * rr) * (dy * dz)
            qmat[2, 0] = (3 - k**2 * rr**2 - 3 * 1j * k * rr) * (dz * dx)

            qmat[1, 0] = qmat[0, 1]
            qmat[2, 1] = qmat[1, 2]
            qmat[0, 2] = qmat[2, 0]

            fout = np.exp(1j * k * rr) / rr**5 / k**2

            fvec = fout * np.dot(qmat, strength)
            evec = evec + fvec
            return evec

        def green3m(x, y, z, source, strength, k):
            # magnetic field corresponding to dyadic green's function
            # due to monochromatic electric dipole located at "source".
            # "strength" is the the intensity of the dipole.
            #  H = curl((I + Hess)(exp(ikr)/r) dot (strength)) =
            #  strength \cross \grad (exp(ikr)/r)
            #
            dx = x - source[0]
            dy = y - source[1]
            dz = z - source[2]
            rr = np.sqrt(dx**2 + dy**2 + dz**2)

            fout = (1 - 1j * k * rr) * np.exp(1j * k * rr) / rr**3
            fvec = np.zeros(3, dtype=np.complex128)
            fvec[0] = fout * dx
            fvec[1] = fout * dy
            fvec[2] = fout * dz

            hvec = np.cross(strength, fvec)

            return hvec

        def dipole3e(x, y, z, source, strength, k):
            #
            #  evalaute electric and magnetic field due
            #  to monochromatic electric dipole located at "source"
            #  with intensity "strength"

            evec = green3e(x, y, z, source, strength, k)
            evec = evec * 1j * k
            hvec = green3m(x, y, z, source, strength, k)
            return evec, hvec

        def dipole3m(x, y, z, source, strength, k):
            #
            #  evalaute electric and magnetic field due
            #  to monochromatic magnetic dipole located at "source"
            #  with intensity "strength"
            evec = green3m(x, y, z, source, strength, k)
            hvec = green3e(x, y, z, source, strength, k)
            hvec = -hvec * 1j * k
            return evec, hvec

        def dipole3eall(x, y, z, sources, strengths, k):
            ns = len(strengths)
            evec = np.zeros(3, dtype=np.complex128)
            hvec = np.zeros(3, dtype=np.complex128)

            for i in range(ns):
                evect, hvect = dipole3e(x, y, z, sources[i], strengths[i], k)
                evec = evec + evect
                hvec = hvec + hvect

        nodes = density_discr.nodes().with_queue(queue).get()
        source = [0.01, -0.03, 0.02]
        #        source = cl.array.to_device(queue,np.zeros(3))
        #        source[0] = 0.01
        #        source[1] =-0.03
        #        source[2] = 0.02
        strength = np.ones(3)

        #        evec = cl.array.to_device(queue,np.zeros((3,len(nodes[0])),dtype=np.complex128))
        #        hvec = cl.array.to_device(queue,np.zeros((3,len(nodes[0])),dtype=np.complex128))

        evec = np.zeros((3, len(nodes[0])), dtype=np.complex128)
        hvec = np.zeros((3, len(nodes[0])), dtype=np.complex128)
        for i in range(len(nodes[0])):
            evec[:, i], hvec[:, i] = dipole3e(nodes[0][i], nodes[1][i],
                                              nodes[2][i], source, strength, k)
        print(np.shape(hvec))
        print(type(evec))
        print(type(hvec))

        evec = cl.array.to_device(queue, evec)
        hvec = cl.array.to_device(queue, hvec)

        bvp_rhs = bind(qbx, sym_rhs)(queue, Einc=evec, Hinc=hvec)
        print(np.shape(bvp_rhs))
        print(type(bvp_rhs))
        #        print(bvp_rhs)
        1 / -1

        bound_op = bind(qbx, sym_operator)

        from pytential.solve import gmres
        if 0:
            gmres_result = gmres(bound_op.scipy_op(queue,
                                                   "sigma",
                                                   dtype=np.complex128,
                                                   k=k),
                                 bvp_rhs,
                                 tol=1e-8,
                                 progress=True,
                                 stall_iterations=0,
                                 hard_failure=True)

            sigma = gmres_result.solution

        fld_at_tgt = bind((qbx, PointsTarget(tgt_points)),
                          sym_repr)(queue, sigma=bvp_rhs, k=k)
        fld_at_tgt = np.array([fi.get() for fi in fld_at_tgt])
        print(fld_at_tgt)
        1 / 0

    # }}}

    #mlab.figure(bgcolor=(1, 1, 1))
    if 1:
        from meshmode.discretization.visualization import make_visualizer
        bdry_vis = make_visualizer(queue, density_discr, target_order)

        bdry_normals = bind(density_discr, sym.normal(3))(queue)\
                .as_vector(dtype=object)

        bdry_vis.write_vtk_file("source.vtu", [
            ("sigma", sigma),
            ("bdry_normals", bdry_normals),
        ])

        fplot = FieldPlotter(bbox_center,
                             extent=2 * bbox_size,
                             npoints=(150, 150, 1))

        qbx_tgt_tol = qbx.copy(target_association_tolerance=0.1)
        from pytential.target import PointsTarget
        from pytential.qbx import QBXTargetAssociationFailedException

        rho_sym = sym.var("rho")

        try:
            fld_in_vol = bind((qbx_tgt_tol, PointsTarget(fplot.points)),
                              sym.make_obj_array([
                                  sym.S(pde_op.kernel,
                                        rho_sym,
                                        k=sym.var("k"),
                                        qbx_forced_limit=None),
                                  sym.d_dx(
                                      3,
                                      sym.S(pde_op.kernel,
                                            rho_sym,
                                            k=sym.var("k"),
                                            qbx_forced_limit=None)),
                                  sym.d_dy(
                                      3,
                                      sym.S(pde_op.kernel,
                                            rho_sym,
                                            k=sym.var("k"),
                                            qbx_forced_limit=None)),
                                  sym.d_dz(
                                      3,
                                      sym.S(pde_op.kernel,
                                            rho_sym,
                                            k=sym.var("k"),
                                            qbx_forced_limit=None)),
                              ]))(queue, jt=jt, rho=rho, k=k)
        except QBXTargetAssociationFailedException as e:
            fplot.write_vtk_file(
                "failed-targets.vts",
                [("failed_targets", e.failed_target_flags.get(queue))])
            raise

        fld_in_vol = sym.make_obj_array([fiv.get() for fiv in fld_in_vol])

        #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
        fplot.write_vtk_file("potential.vts", [
            ("potential", fld_in_vol[0]),
            ("grad", fld_in_vol[1:]),
        ])
예제 #5
0
def run_int_eq_test(cl_ctx, queue, case, resolution, visualize):
    mesh = case.get_mesh(resolution, case.target_order)
    print("%d elements" % mesh.nelements)

    from pytential.qbx import QBXLayerPotentialSource
    from meshmode.discretization import Discretization
    from meshmode.discretization.poly_element import \
            InterpolatoryQuadratureSimplexGroupFactory
    pre_density_discr = Discretization(
            cl_ctx, mesh,
            InterpolatoryQuadratureSimplexGroupFactory(case.target_order))

    source_order = 4*case.target_order

    refiner_extra_kwargs = {}

    qbx_lpot_kwargs = {}
    if case.fmm_backend is None:
        qbx_lpot_kwargs["fmm_order"] = False
    else:
        if hasattr(case, "fmm_tol"):
            from sumpy.expansion.level_to_order import SimpleExpansionOrderFinder
            qbx_lpot_kwargs["fmm_level_to_order"] = SimpleExpansionOrderFinder(
                    case.fmm_tol)

        elif hasattr(case, "fmm_order"):
            qbx_lpot_kwargs["fmm_order"] = case.fmm_order
        else:
            qbx_lpot_kwargs["fmm_order"] = case.qbx_order + 5

    qbx = QBXLayerPotentialSource(
            pre_density_discr,
            fine_order=source_order,
            qbx_order=case.qbx_order,

            _box_extent_norm=getattr(case, "box_extent_norm", None),
            _from_sep_smaller_crit=getattr(case, "from_sep_smaller_crit", None),
            _from_sep_smaller_min_nsources_cumul=30,
            fmm_backend=case.fmm_backend, **qbx_lpot_kwargs)

    if case.use_refinement:
        if case.k != 0 and getattr(case, "refine_on_helmholtz_k", True):
            refiner_extra_kwargs["kernel_length_scale"] = 5/case.k

        if hasattr(case, "scaled_max_curvature_threshold"):
            refiner_extra_kwargs["_scaled_max_curvature_threshold"] = \
                    case.scaled_max_curvature_threshold

        if hasattr(case, "expansion_disturbance_tolerance"):
            refiner_extra_kwargs["_expansion_disturbance_tolerance"] = \
                    case.expansion_disturbance_tolerance

        if hasattr(case, "refinement_maxiter"):
            refiner_extra_kwargs["maxiter"] = case.refinement_maxiter

        #refiner_extra_kwargs["visualize"] = True

        print("%d elements before refinement" % pre_density_discr.mesh.nelements)
        qbx, _ = qbx.with_refinement(**refiner_extra_kwargs)
        print("%d stage-1 elements after refinement"
                % qbx.density_discr.mesh.nelements)
        print("%d stage-2 elements after refinement"
                % qbx.stage2_density_discr.mesh.nelements)
        print("quad stage-2 elements have %d nodes"
                % qbx.quad_stage2_density_discr.groups[0].nunit_nodes)

    density_discr = qbx.density_discr

    if hasattr(case, "visualize_geometry") and case.visualize_geometry:
        bdry_normals = bind(
                density_discr, sym.normal(mesh.ambient_dim)
                )(queue).as_vector(dtype=object)

        bdry_vis = make_visualizer(queue, density_discr, case.target_order)
        bdry_vis.write_vtk_file("geometry.vtu", [
            ("normals", bdry_normals)
            ])

    # {{{ plot geometry

    if 0:
        if mesh.ambient_dim == 2:
            # show geometry, centers, normals
            nodes_h = density_discr.nodes().get(queue=queue)
            pt.plot(nodes_h[0], nodes_h[1], "x-")
            normal = bind(density_discr, sym.normal(2))(queue).as_vector(np.object)
            pt.quiver(nodes_h[0], nodes_h[1],
                    normal[0].get(queue), normal[1].get(queue))
            pt.gca().set_aspect("equal")
            pt.show()

        elif mesh.ambient_dim == 3:
            bdry_vis = make_visualizer(queue, density_discr, case.target_order+3)

            bdry_normals = bind(density_discr, sym.normal(3))(queue)\
                    .as_vector(dtype=object)

            bdry_vis.write_vtk_file("pre-solve-source-%s.vtu" % resolution, [
                ("bdry_normals", bdry_normals),
                ])

        else:
            raise ValueError("invalid mesh dim")

    # }}}

    # {{{ set up operator

    from pytential.symbolic.pde.scalar import (
            DirichletOperator,
            NeumannOperator)

    from sumpy.kernel import LaplaceKernel, HelmholtzKernel
    if case.k:
        knl = HelmholtzKernel(mesh.ambient_dim)
        knl_kwargs = {"k": sym.var("k")}
        concrete_knl_kwargs = {"k": case.k}
    else:
        knl = LaplaceKernel(mesh.ambient_dim)
        knl_kwargs = {}
        concrete_knl_kwargs = {}

    if knl.is_complex_valued:
        dtype = np.complex128
    else:
        dtype = np.float64

    loc_sign = +1 if case.prob_side in [+1, "scat"] else -1

    if case.bc_type == "dirichlet":
        op = DirichletOperator(knl, loc_sign, use_l2_weighting=True,
                kernel_arguments=knl_kwargs)
    elif case.bc_type == "neumann":
        op = NeumannOperator(knl, loc_sign, use_l2_weighting=True,
                 use_improved_operator=False, kernel_arguments=knl_kwargs)
    else:
        assert False

    op_u = op.operator(sym.var("u"))

    # }}}

    # {{{ set up test data

    if case.prob_side == -1:
        test_src_geo_radius = case.outer_radius
        test_tgt_geo_radius = case.inner_radius
    elif case.prob_side == +1:
        test_src_geo_radius = case.inner_radius
        test_tgt_geo_radius = case.outer_radius
    elif case.prob_side == "scat":
        test_src_geo_radius = case.outer_radius
        test_tgt_geo_radius = case.outer_radius
    else:
        raise ValueError("unknown problem_side")

    point_sources = make_circular_point_group(
            mesh.ambient_dim, 10, test_src_geo_radius,
            func=lambda x: x**1.5)
    test_targets = make_circular_point_group(
            mesh.ambient_dim, 20, test_tgt_geo_radius)

    np.random.seed(22)
    source_charges = np.random.randn(point_sources.shape[1])
    source_charges[-1] = -np.sum(source_charges[:-1])
    source_charges = source_charges.astype(dtype)
    assert np.sum(source_charges) < 1e-15

    source_charges_dev = cl.array.to_device(queue, source_charges)

    # }}}

    # {{{ establish BCs

    from pytential.source import PointPotentialSource
    from pytential.target import PointsTarget

    point_source = PointPotentialSource(cl_ctx, point_sources)

    pot_src = sym.IntG(
        # FIXME: qbx_forced_limit--really?
        knl, sym.var("charges"), qbx_forced_limit=None, **knl_kwargs)

    test_direct = bind((point_source, PointsTarget(test_targets)), pot_src)(
            queue, charges=source_charges_dev, **concrete_knl_kwargs)

    if case.bc_type == "dirichlet":
        bc = bind((point_source, density_discr), pot_src)(
                queue, charges=source_charges_dev, **concrete_knl_kwargs)

    elif case.bc_type == "neumann":
        bc = bind(
                (point_source, density_discr),
                sym.normal_derivative(
                    qbx.ambient_dim, pot_src, where=sym.DEFAULT_TARGET)
                )(queue, charges=source_charges_dev, **concrete_knl_kwargs)

    # }}}

    # {{{ solve

    bound_op = bind(qbx, op_u)

    rhs = bind(density_discr, op.prepare_rhs(sym.var("bc")))(queue, bc=bc)

    try:
        from pytential.solve import gmres
        gmres_result = gmres(
                bound_op.scipy_op(queue, "u", dtype, **concrete_knl_kwargs),
                rhs,
                tol=case.gmres_tol,
                progress=True,
                hard_failure=True,
                stall_iterations=50, no_progress_factor=1.05)
    except QBXTargetAssociationFailedException as e:
        bdry_vis = make_visualizer(queue, density_discr, case.target_order+3)

        bdry_vis.write_vtk_file("failed-targets-%s.vtu" % resolution, [
            ("failed_targets", e.failed_target_flags),
            ])
        raise

    print("gmres state:", gmres_result.state)
    weighted_u = gmres_result.solution

    # }}}

    # {{{ build matrix for spectrum check

    if 0:
        from sumpy.tools import build_matrix
        mat = build_matrix(
                bound_op.scipy_op(
                    queue, arg_name="u", dtype=dtype, k=case.k))
        w, v = la.eig(mat)
        if 0:
            pt.imshow(np.log10(1e-20+np.abs(mat)))
            pt.colorbar()
            pt.show()

        #assert abs(s[-1]) < 1e-13, "h
        #assert abs(s[-2]) > 1e-7
        #from pudb import set_trace; set_trace()

    # }}}

    if case.prob_side != "scat":
        # {{{ error check

        points_target = PointsTarget(test_targets)
        bound_tgt_op = bind((qbx, points_target),
                op.representation(sym.var("u")))

        test_via_bdry = bound_tgt_op(queue, u=weighted_u, k=case.k)

        err = test_via_bdry - test_direct

        err = err.get()
        test_direct = test_direct.get()
        test_via_bdry = test_via_bdry.get()

        # {{{ remove effect of net source charge

        if case.k == 0 and case.bc_type == "neumann" and loc_sign == -1:

            # remove constant offset in interior Laplace Neumann error
            tgt_ones = np.ones_like(test_direct)
            tgt_ones = tgt_ones/la.norm(tgt_ones)
            err = err - np.vdot(tgt_ones, err)*tgt_ones

        # }}}

        rel_err_2 = la.norm(err)/la.norm(test_direct)
        rel_err_inf = la.norm(err, np.inf)/la.norm(test_direct, np.inf)

        # }}}

        print("rel_err_2: %g rel_err_inf: %g" % (rel_err_2, rel_err_inf))

    else:
        rel_err_2 = None
        rel_err_inf = None

    # {{{ test gradient

    if case.check_gradient and case.prob_side != "scat":
        bound_grad_op = bind((qbx, points_target),
                op.representation(
                    sym.var("u"),
                    map_potentials=lambda pot: sym.grad(mesh.ambient_dim, pot),
                    qbx_forced_limit=None))

        #print(bound_t_deriv_op.code)

        grad_from_src = bound_grad_op(
                queue, u=weighted_u, **concrete_knl_kwargs)

        grad_ref = (bind(
                (point_source, points_target),
                sym.grad(mesh.ambient_dim, pot_src)
                )(queue, charges=source_charges_dev, **concrete_knl_kwargs)
                )

        grad_err = (grad_from_src - grad_ref)

        rel_grad_err_inf = (
                la.norm(grad_err[0].get(), np.inf)
                / la.norm(grad_ref[0].get(), np.inf))

        print("rel_grad_err_inf: %g" % rel_grad_err_inf)

    # }}}

    # {{{ test tangential derivative

    if case.check_tangential_deriv and case.prob_side != "scat":
        bound_t_deriv_op = bind(qbx,
                op.representation(
                    sym.var("u"),
                    map_potentials=lambda pot: sym.tangential_derivative(2, pot),
                    qbx_forced_limit=loc_sign))

        #print(bound_t_deriv_op.code)

        tang_deriv_from_src = bound_t_deriv_op(
                queue, u=weighted_u, **concrete_knl_kwargs).as_scalar().get()

        tang_deriv_ref = (bind(
                (point_source, density_discr),
                sym.tangential_derivative(2, pot_src)
                )(queue, charges=source_charges_dev, **concrete_knl_kwargs)
                .as_scalar().get())

        if 0:
            pt.plot(tang_deriv_ref.real)
            pt.plot(tang_deriv_from_src.real)
            pt.show()

        td_err = (tang_deriv_from_src - tang_deriv_ref)

        rel_td_err_inf = la.norm(td_err, np.inf)/la.norm(tang_deriv_ref, np.inf)

        print("rel_td_err_inf: %g" % rel_td_err_inf)

    else:
        rel_td_err_inf = None

    # }}}

    # {{{ any-D file plotting

    if visualize:
        bdry_vis = make_visualizer(queue, density_discr, case.target_order+3)

        bdry_normals = bind(density_discr, sym.normal(qbx.ambient_dim))(queue)\
                .as_vector(dtype=object)

        sym_sqrt_j = sym.sqrt_jac_q_weight(density_discr.ambient_dim)
        u = bind(density_discr, sym.var("u")/sym_sqrt_j)(queue, u=weighted_u)

        bdry_vis.write_vtk_file("source-%s.vtu" % resolution, [
            ("u", u),
            ("bc", bc),
            #("bdry_normals", bdry_normals),
            ])

        from sumpy.visualization import make_field_plotter_from_bbox  # noqa
        from meshmode.mesh.processing import find_bounding_box

        vis_grid_spacing = (0.1, 0.1, 0.1)[:qbx.ambient_dim]
        if hasattr(case, "vis_grid_spacing"):
            vis_grid_spacing = case.vis_grid_spacing
        vis_extend_factor = 0.2
        if hasattr(case, "vis_extend_factor"):
            vis_grid_spacing = case.vis_grid_spacing

        fplot = make_field_plotter_from_bbox(
                find_bounding_box(mesh),
                h=vis_grid_spacing,
                extend_factor=vis_extend_factor)

        qbx_tgt_tol = qbx.copy(target_association_tolerance=0.15)
        from pytential.target import PointsTarget

        try:
            solved_pot = bind(
                    (qbx_tgt_tol, PointsTarget(fplot.points)),
                    op.representation(sym.var("u"))
                    )(queue, u=weighted_u, k=case.k)
        except QBXTargetAssociationFailedException as e:
            fplot.write_vtk_file(
                    "failed-targets.vts",
                    [
                        ("failed_targets", e.failed_target_flags.get(queue))
                        ])
            raise

        from sumpy.kernel import LaplaceKernel
        ones_density = density_discr.zeros(queue)
        ones_density.fill(1)
        indicator = bind(
                (qbx_tgt_tol, PointsTarget(fplot.points)),
                -sym.D(LaplaceKernel(density_discr.ambient_dim),
                    sym.var("sigma"),
                    qbx_forced_limit=None))(
                queue, sigma=ones_density).get()

        solved_pot = solved_pot.get()

        true_pot = bind((point_source, PointsTarget(fplot.points)), pot_src)(
                queue, charges=source_charges_dev, **concrete_knl_kwargs).get()

        #fplot.show_scalar_in_mayavi(solved_pot.real, max_val=5)
        if case.prob_side == "scat":
            fplot.write_vtk_file(
                    "potential-%s.vts" % resolution,
                    [
                        ("pot_scattered", solved_pot),
                        ("pot_incoming", -true_pot),
                        ("indicator", indicator),
                        ]
                    )
        else:
            fplot.write_vtk_file(
                    "potential-%s.vts" % resolution,
                    [
                        ("solved_pot", solved_pot),
                        ("true_pot", true_pot),
                        ("indicator", indicator),
                        ]
                    )

    # }}}

    class Result(Record):
        pass

    return Result(
            h_max=qbx.h_max,
            rel_err_2=rel_err_2,
            rel_err_inf=rel_err_inf,
            rel_td_err_inf=rel_td_err_inf,
            gmres_result=gmres_result)
예제 #6
0
def main():
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

    cl_ctx = cl.create_some_context()
    queue = cl.CommandQueue(cl_ctx)

    from meshmode.mesh.generation import ellipse, make_curve_mesh
    from functools import partial

    if 0:
        mesh = make_curve_mesh(partial(ellipse, 1),
                               np.linspace(0, 1, nelements + 1), mesh_order)
    else:
        base_mesh = make_curve_mesh(partial(ellipse, 1),
                                    np.linspace(0, 1, nelements + 1),
                                    mesh_order)

        from meshmode.mesh.processing import affine_map, merge_disjoint_meshes
        nx = 2
        ny = 2
        dx = 2 / nx
        meshes = [
            affine_map(base_mesh,
                       A=np.diag([dx * 0.25, dx * 0.25]),
                       b=np.array([dx * (ix - nx / 2), dx * (iy - ny / 2)]))
            for ix in range(nx) for iy in range(ny)
        ]

        mesh = merge_disjoint_meshes(meshes, single_group=True)

        if 0:
            from meshmode.mesh.visualization import draw_curve
            draw_curve(mesh)
            import matplotlib.pyplot as plt
            plt.show()

    pre_density_discr = Discretization(
        cl_ctx, mesh,
        InterpolatoryQuadratureSimplexGroupFactory(bdry_quad_order))

    from pytential.qbx import (QBXLayerPotentialSource,
                               QBXTargetAssociationFailedException)
    qbx, _ = QBXLayerPotentialSource(pre_density_discr,
                                     fine_order=bdry_ovsmp_quad_order,
                                     qbx_order=qbx_order,
                                     fmm_order=fmm_order).with_refinement()
    density_discr = qbx.density_discr

    # {{{ describe bvp

    from sumpy.kernel import LaplaceKernel, HelmholtzKernel
    kernel = HelmholtzKernel(2)

    cse = sym.cse

    sigma_sym = sym.var("sigma")
    sqrt_w = sym.sqrt_jac_q_weight(2)
    inv_sqrt_w_sigma = cse(sigma_sym / sqrt_w)

    # Brakhage-Werner parameter
    alpha = 1j

    # -1 for interior Dirichlet
    # +1 for exterior Dirichlet
    loc_sign = +1

    bdry_op_sym = (-loc_sign * 0.5 * sigma_sym + sqrt_w * (alpha * sym.S(
        kernel, inv_sqrt_w_sigma, k=sym.var("k"), qbx_forced_limit=+1) - sym.D(
            kernel, inv_sqrt_w_sigma, k=sym.var("k"), qbx_forced_limit="avg")))

    # }}}

    bound_op = bind(qbx, bdry_op_sym)

    # {{{ fix rhs and solve

    nodes = density_discr.nodes().with_queue(queue)
    k_vec = np.array([2, 1])
    k_vec = k * k_vec / la.norm(k_vec, 2)

    def u_incoming_func(x):
        return cl.clmath.exp(1j * (x[0] * k_vec[0] + x[1] * k_vec[1]))

    bc = -u_incoming_func(nodes)

    bvp_rhs = bind(qbx, sqrt_w * sym.var("bc"))(queue, bc=bc)

    from pytential.solve import gmres
    gmres_result = gmres(bound_op.scipy_op(queue,
                                           "sigma",
                                           dtype=np.complex128,
                                           k=k),
                         bvp_rhs,
                         tol=1e-8,
                         progress=True,
                         stall_iterations=0,
                         hard_failure=True)

    # }}}

    # {{{ postprocess/visualize

    sigma = gmres_result.solution

    repr_kwargs = dict(k=sym.var("k"), qbx_forced_limit=None)
    representation_sym = (
        alpha * sym.S(kernel, inv_sqrt_w_sigma, **repr_kwargs) -
        sym.D(kernel, inv_sqrt_w_sigma, **repr_kwargs))

    from sumpy.visualization import FieldPlotter
    fplot = FieldPlotter(np.zeros(2), extent=5, npoints=500)

    targets = cl.array.to_device(queue, fplot.points)

    u_incoming = u_incoming_func(targets)

    qbx_stick_out = qbx.copy(target_association_tolerance=0.05)

    ones_density = density_discr.zeros(queue)
    ones_density.fill(1)
    indicator = bind((qbx_stick_out, PointsTarget(targets)),
                     sym.D(LaplaceKernel(2),
                           sym.var("sigma"),
                           qbx_forced_limit=None))(queue,
                                                   sigma=ones_density).get()

    try:
        fld_in_vol = bind((qbx_stick_out, PointsTarget(targets)),
                          representation_sym)(queue, sigma=sigma, k=k).get()
    except QBXTargetAssociationFailedException as e:
        fplot.write_vtk_file("failed-targets.vts",
                             [("failed", e.failed_target_flags.get(queue))])
        raise

    #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
    fplot.write_vtk_file("potential-helm.vts", [
        ("potential", fld_in_vol),
        ("indicator", indicator),
        ("u_incoming", u_incoming.get()),
    ])
예제 #7
0
def main(mesh_name="torus", visualize=False):
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

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

    if mesh_name == "torus":
        rout = 10
        rin = 1

        from meshmode.mesh.generation import generate_torus
        base_mesh = generate_torus(
                rout, rin, 40, 4,
                mesh_order)

        from meshmode.mesh.processing import affine_map, merge_disjoint_meshes
        # nx = 1
        # ny = 1
        nz = 1
        dz = 0
        meshes = [
                affine_map(
                    base_mesh,
                    A=np.diag([1, 1, 1]),
                    b=np.array([0, 0, iz*dz]))
                for iz in range(nz)]

        mesh = merge_disjoint_meshes(meshes, single_group=True)

        if visualize:
            from meshmode.mesh.visualization import draw_curve
            draw_curve(mesh)
            import matplotlib.pyplot as plt
            plt.show()
    else:
        raise ValueError(f"unknown mesh name: {mesh_name}")

    pre_density_discr = Discretization(
            actx, mesh,
            InterpolatoryQuadratureSimplexGroupFactory(bdry_quad_order))

    from pytential.qbx import (
            QBXLayerPotentialSource, QBXTargetAssociationFailedException)
    qbx = QBXLayerPotentialSource(
            pre_density_discr, fine_order=bdry_ovsmp_quad_order, qbx_order=qbx_order,
            fmm_order=fmm_order,
            )

    from sumpy.visualization import FieldPlotter
    fplot = FieldPlotter(np.zeros(3), extent=20, npoints=50)
    targets = actx.from_numpy(fplot.points)

    from pytential import GeometryCollection
    places = GeometryCollection({
        "qbx": qbx,
        "qbx_target_assoc": qbx.copy(target_association_tolerance=0.2),
        "targets": PointsTarget(targets)
        }, auto_where="qbx")
    density_discr = places.get_discretization("qbx")

    # {{{ describe bvp

    from sumpy.kernel import LaplaceKernel
    kernel = LaplaceKernel(3)

    sigma_sym = sym.var("sigma")
    #sqrt_w = sym.sqrt_jac_q_weight(3)
    sqrt_w = 1
    inv_sqrt_w_sigma = sym.cse(sigma_sym/sqrt_w)

    # -1 for interior Dirichlet
    # +1 for exterior Dirichlet
    loc_sign = +1

    bdry_op_sym = (loc_sign*0.5*sigma_sym
            + sqrt_w*(
                sym.S(kernel, inv_sqrt_w_sigma, qbx_forced_limit=+1)
                + sym.D(kernel, inv_sqrt_w_sigma, qbx_forced_limit="avg")
                ))

    # }}}

    bound_op = bind(places, bdry_op_sym)

    # {{{ fix rhs and solve

    from meshmode.dof_array import thaw, flatten, unflatten
    nodes = thaw(actx, density_discr.nodes())
    source = np.array([rout, 0, 0])

    def u_incoming_func(x):
        from pytools.obj_array import obj_array_vectorize
        x = obj_array_vectorize(actx.to_numpy, flatten(x))
        x = np.array(list(x))
        #        return 1/cl.clmath.sqrt( (x[0] - source[0])**2
        #                                +(x[1] - source[1])**2
        #                                +(x[2] - source[2])**2 )
        return 1.0/la.norm(x - source[:, None], axis=0)

    bc = unflatten(actx,
            density_discr,
            actx.from_numpy(u_incoming_func(nodes)))

    bvp_rhs = bind(places, sqrt_w*sym.var("bc"))(actx, bc=bc)

    from pytential.solve import gmres
    gmres_result = gmres(
            bound_op.scipy_op(actx, "sigma", dtype=np.float64),
            bvp_rhs, tol=1e-14, progress=True,
            stall_iterations=0,
            hard_failure=True)

    sigma = bind(places, sym.var("sigma")/sqrt_w)(
            actx, sigma=gmres_result.solution)

    # }}}

    from meshmode.discretization.visualization import make_visualizer
    bdry_vis = make_visualizer(actx, density_discr, 20)
    bdry_vis.write_vtk_file("laplace.vtu", [
        ("sigma", sigma),
        ])

    # {{{ postprocess/visualize

    repr_kwargs = dict(
            source="qbx_target_assoc",
            target="targets",
            qbx_forced_limit=None)
    representation_sym = (
            sym.S(kernel, inv_sqrt_w_sigma, **repr_kwargs)
            + sym.D(kernel, inv_sqrt_w_sigma, **repr_kwargs))

    try:
        fld_in_vol = actx.to_numpy(
                bind(places, representation_sym)(actx, sigma=sigma))
    except QBXTargetAssociationFailedException as e:
        fplot.write_vtk_file("laplace-dirichlet-3d-failed-targets.vts", [
            ("failed", e.failed_target_flags.get(queue)),
            ])
        raise

    #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
    fplot.write_vtk_file("laplace-dirichlet-3d-potential.vts", [
        ("potential", fld_in_vol),
        ])
예제 #8
0
def main(mesh_name="ellipse", visualize=False):
    import logging
    logging.basicConfig(level=logging.INFO)  # INFO for more progress info

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

    from meshmode.mesh.generation import ellipse, make_curve_mesh
    from functools import partial

    if mesh_name == "ellipse":
        mesh = make_curve_mesh(partial(ellipse, 1),
                               np.linspace(0, 1, nelements + 1), mesh_order)
    elif mesh_name == "ellipse_array":
        base_mesh = make_curve_mesh(partial(ellipse, 1),
                                    np.linspace(0, 1, nelements + 1),
                                    mesh_order)

        from meshmode.mesh.processing import affine_map, merge_disjoint_meshes
        nx = 2
        ny = 2
        dx = 2 / nx
        meshes = [
            affine_map(base_mesh,
                       A=np.diag([dx * 0.25, dx * 0.25]),
                       b=np.array([dx * (ix - nx / 2), dx * (iy - ny / 2)]))
            for ix in range(nx) for iy in range(ny)
        ]

        mesh = merge_disjoint_meshes(meshes, single_group=True)

        if visualize:
            from meshmode.mesh.visualization import draw_curve
            draw_curve(mesh)
            import matplotlib.pyplot as plt
            plt.show()
    else:
        raise ValueError(f"unknown mesh name: {mesh_name}")

    pre_density_discr = Discretization(
        actx, mesh,
        InterpolatoryQuadratureSimplexGroupFactory(bdry_quad_order))

    from pytential.qbx import (QBXLayerPotentialSource,
                               QBXTargetAssociationFailedException)
    qbx = QBXLayerPotentialSource(pre_density_discr,
                                  fine_order=bdry_ovsmp_quad_order,
                                  qbx_order=qbx_order,
                                  fmm_order=fmm_order)

    from sumpy.visualization import FieldPlotter
    fplot = FieldPlotter(np.zeros(2), extent=5, npoints=500)
    targets = actx.from_numpy(fplot.points)

    from pytential import GeometryCollection
    places = GeometryCollection(
        {
            "qbx":
            qbx,
            "qbx_high_target_assoc_tol":
            qbx.copy(target_association_tolerance=0.05),
            "targets":
            PointsTarget(targets)
        },
        auto_where="qbx")
    density_discr = places.get_discretization("qbx")

    # {{{ describe bvp

    from sumpy.kernel import LaplaceKernel, HelmholtzKernel
    kernel = HelmholtzKernel(2)

    sigma_sym = sym.var("sigma")
    sqrt_w = sym.sqrt_jac_q_weight(2)
    inv_sqrt_w_sigma = sym.cse(sigma_sym / sqrt_w)

    # Brakhage-Werner parameter
    alpha = 1j

    # -1 for interior Dirichlet
    # +1 for exterior Dirichlet
    loc_sign = +1

    k_sym = sym.var("k")
    bdry_op_sym = (
        -loc_sign * 0.5 * sigma_sym + sqrt_w *
        (alpha * sym.S(kernel, inv_sqrt_w_sigma, k=k_sym, qbx_forced_limit=+1)
         - sym.D(kernel, inv_sqrt_w_sigma, k=k_sym, qbx_forced_limit="avg")))

    # }}}

    bound_op = bind(places, bdry_op_sym)

    # {{{ fix rhs and solve

    from meshmode.dof_array import thaw
    nodes = thaw(actx, density_discr.nodes())
    k_vec = np.array([2, 1])
    k_vec = k * k_vec / la.norm(k_vec, 2)

    def u_incoming_func(x):
        return actx.np.exp(1j * (x[0] * k_vec[0] + x[1] * k_vec[1]))

    bc = -u_incoming_func(nodes)

    bvp_rhs = bind(places, sqrt_w * sym.var("bc"))(actx, bc=bc)

    from pytential.solve import gmres
    gmres_result = gmres(bound_op.scipy_op(actx,
                                           sigma_sym.name,
                                           dtype=np.complex128,
                                           k=k),
                         bvp_rhs,
                         tol=1e-8,
                         progress=True,
                         stall_iterations=0,
                         hard_failure=True)

    # }}}

    # {{{ postprocess/visualize

    repr_kwargs = dict(source="qbx_high_target_assoc_tol",
                       target="targets",
                       qbx_forced_limit=None)
    representation_sym = (
        alpha * sym.S(kernel, inv_sqrt_w_sigma, k=k_sym, **repr_kwargs) -
        sym.D(kernel, inv_sqrt_w_sigma, k=k_sym, **repr_kwargs))

    u_incoming = u_incoming_func(targets)
    ones_density = density_discr.zeros(actx)
    for elem in ones_density:
        elem.fill(1)

    indicator = actx.to_numpy(
        bind(places, sym.D(LaplaceKernel(2), sigma_sym,
                           **repr_kwargs))(actx, sigma=ones_density))

    try:
        fld_in_vol = actx.to_numpy(
            bind(places, representation_sym)(actx,
                                             sigma=gmres_result.solution,
                                             k=k))
    except QBXTargetAssociationFailedException as e:
        fplot.write_vtk_file("helmholtz-dirichlet-failed-targets.vts",
                             [("failed", e.failed_target_flags.get(queue))])
        raise

    #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
    fplot.write_vtk_file("helmholtz-dirichlet-potential.vts", [
        ("potential", fld_in_vol),
        ("indicator", indicator),
        ("u_incoming", actx.to_numpy(u_incoming)),
    ])
예제 #9
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def main():
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

    cl_ctx = cl.create_some_context()
    queue = cl.CommandQueue(cl_ctx)

    target_order = 16
    qbx_order = 3
    nelements = 60
    mode_nr = 0

    k = 0
    if k:
        kernel = HelmholtzKernel(2)
    else:
        kernel = LaplaceKernel(2)
    #kernel = OneKernel()

    mesh = make_curve_mesh(
            #lambda t: ellipse(1, t),
            starfish,
            np.linspace(0, 1, nelements+1),
            target_order)

    from pytential.qbx import QBXLayerPotentialSource
    from meshmode.discretization import Discretization
    from meshmode.discretization.poly_element import \
            InterpolatoryQuadratureSimplexGroupFactory

    pre_density_discr = Discretization(
            cl_ctx, mesh,
            InterpolatoryQuadratureSimplexGroupFactory(target_order))

    slow_qbx, _ = QBXLayerPotentialSource(
            pre_density_discr, fine_order=2*target_order,
            qbx_order=qbx_order, fmm_order=False,
            target_association_tolerance=.05
            ).with_refinement()
    qbx = slow_qbx.copy(fmm_order=10)
    density_discr = slow_qbx.density_discr

    nodes = density_discr.nodes().with_queue(queue)

    angle = cl.clmath.atan2(nodes[1], nodes[0])

    from pytential import bind, sym
    #op = sym.d_dx(sym.S(kernel, sym.var("sigma")), qbx_forced_limit=None)
    #op = sym.D(kernel, sym.var("sigma"), qbx_forced_limit=None)
    op = sym.S(kernel, sym.var("sigma"), qbx_forced_limit=None)

    sigma = cl.clmath.cos(mode_nr*angle)

    if isinstance(kernel, HelmholtzKernel):
        sigma = sigma.astype(np.complex128)

    fplot = FieldPlotter(np.zeros(2), extent=5, npoints=600)
    from pytential.target import PointsTarget

    fld_in_vol = bind(
            (slow_qbx, PointsTarget(fplot.points)),
            op)(queue, sigma=sigma, k=k).get()

    fmm_fld_in_vol = bind(
            (qbx, PointsTarget(fplot.points)),
            op)(queue, sigma=sigma, k=k).get()

    err = fmm_fld_in_vol-fld_in_vol

    import matplotlib
    matplotlib.use('Agg')
    im = fplot.show_scalar_in_matplotlib(np.log10(np.abs(err) + 1e-17))

    from matplotlib.colors import Normalize
    im.set_norm(Normalize(vmin=-12, vmax=0))

    import matplotlib.pyplot as pt
    from matplotlib.ticker import NullFormatter
    pt.gca().xaxis.set_major_formatter(NullFormatter())
    pt.gca().yaxis.set_major_formatter(NullFormatter())

    cb = pt.colorbar(shrink=0.9)
    cb.set_label(r"$\log_{10}(\mathdefault{Error})$")

    pt.savefig("fmm-error-order-%d.pdf" % qbx_order)
예제 #10
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def main():
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

    cl_ctx = cl.create_some_context()
    queue = cl.CommandQueue(cl_ctx)

    target_order = 16
    qbx_order = 3
    nelements = 60
    mode_nr = 0

    k = 0
    if k:
        kernel = HelmholtzKernel(2)
    else:
        kernel = LaplaceKernel(2)
    #kernel = OneKernel()

    mesh = make_curve_mesh(
        #lambda t: ellipse(1, t),
        starfish,
        np.linspace(0, 1, nelements + 1),
        target_order)

    from pytential.qbx import QBXLayerPotentialSource
    from meshmode.discretization import Discretization
    from meshmode.discretization.poly_element import \
            InterpolatoryQuadratureSimplexGroupFactory

    pre_density_discr = Discretization(
        cl_ctx, mesh, InterpolatoryQuadratureSimplexGroupFactory(target_order))

    slow_qbx, _ = QBXLayerPotentialSource(
        pre_density_discr,
        fine_order=2 * target_order,
        qbx_order=qbx_order,
        fmm_order=False,
        target_association_tolerance=.05).with_refinement()
    qbx = slow_qbx.copy(fmm_order=10)
    density_discr = slow_qbx.density_discr

    nodes = density_discr.nodes().with_queue(queue)

    angle = cl.clmath.atan2(nodes[1], nodes[0])

    from pytential import bind, sym
    #op = sym.d_dx(sym.S(kernel, sym.var("sigma")), qbx_forced_limit=None)
    #op = sym.D(kernel, sym.var("sigma"), qbx_forced_limit=None)
    op = sym.S(kernel, sym.var("sigma"), qbx_forced_limit=None)

    sigma = cl.clmath.cos(mode_nr * angle)

    if isinstance(kernel, HelmholtzKernel):
        sigma = sigma.astype(np.complex128)

    fplot = FieldPlotter(np.zeros(2), extent=5, npoints=600)
    from pytential.target import PointsTarget

    fld_in_vol = bind((slow_qbx, PointsTarget(fplot.points)), op)(queue,
                                                                  sigma=sigma,
                                                                  k=k).get()

    fmm_fld_in_vol = bind((qbx, PointsTarget(fplot.points)), op)(queue,
                                                                 sigma=sigma,
                                                                 k=k).get()

    err = fmm_fld_in_vol - fld_in_vol

    import matplotlib
    matplotlib.use('Agg')
    im = fplot.show_scalar_in_matplotlib(np.log10(np.abs(err) + 1e-17))

    from matplotlib.colors import Normalize
    im.set_norm(Normalize(vmin=-12, vmax=0))

    import matplotlib.pyplot as pt
    from matplotlib.ticker import NullFormatter
    pt.gca().xaxis.set_major_formatter(NullFormatter())
    pt.gca().yaxis.set_major_formatter(NullFormatter())

    cb = pt.colorbar(shrink=0.9)
    cb.set_label(r"$\log_{10}(\mathdefault{Error})$")

    pt.savefig("fmm-error-order-%d.pdf" % qbx_order)
예제 #11
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def main():
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

    cl_ctx = cl.create_some_context()
    queue = cl.CommandQueue(cl_ctx)

    from meshmode.mesh.generation import generate_torus

    rout = 10
    rin = 1
    if 1:
        base_mesh = generate_torus(rout, rin, 40, 4, mesh_order)

        from meshmode.mesh.processing import affine_map, merge_disjoint_meshes
        # nx = 1
        # ny = 1
        nz = 1
        dz = 0
        meshes = [
            affine_map(base_mesh,
                       A=np.diag([1, 1, 1]),
                       b=np.array([0, 0, iz * dz])) for iz in range(nz)
        ]

        mesh = merge_disjoint_meshes(meshes, single_group=True)

        if 0:
            from meshmode.mesh.visualization import draw_curve
            draw_curve(mesh)
            import matplotlib.pyplot as plt
            plt.show()

    pre_density_discr = Discretization(
        cl_ctx, mesh,
        InterpolatoryQuadratureSimplexGroupFactory(bdry_quad_order))

    from pytential.qbx import (QBXLayerPotentialSource,
                               QBXTargetAssociationFailedException)
    qbx, _ = QBXLayerPotentialSource(
        pre_density_discr,
        fine_order=bdry_ovsmp_quad_order,
        qbx_order=qbx_order,
        fmm_order=fmm_order,
    ).with_refinement()
    density_discr = qbx.density_discr

    # {{{ describe bvp

    from sumpy.kernel import LaplaceKernel
    kernel = LaplaceKernel(3)

    cse = sym.cse

    sigma_sym = sym.var("sigma")
    #sqrt_w = sym.sqrt_jac_q_weight(3)
    sqrt_w = 1
    inv_sqrt_w_sigma = cse(sigma_sym / sqrt_w)

    # -1 for interior Dirichlet
    # +1 for exterior Dirichlet
    loc_sign = +1

    bdry_op_sym = (
        loc_sign * 0.5 * sigma_sym + sqrt_w *
        (sym.S(kernel, inv_sqrt_w_sigma) + sym.D(kernel, inv_sqrt_w_sigma)))

    # }}}

    bound_op = bind(qbx, bdry_op_sym)

    # {{{ fix rhs and solve

    nodes = density_discr.nodes().with_queue(queue)
    source = np.array([rout, 0, 0])

    def u_incoming_func(x):
        #        return 1/cl.clmath.sqrt( (x[0] - source[0])**2
        #                                +(x[1] - source[1])**2
        #                                +(x[2] - source[2])**2 )
        return 1.0 / la.norm(x.get() - source[:, None], axis=0)

    bc = cl.array.to_device(queue, u_incoming_func(nodes))

    bvp_rhs = bind(qbx, sqrt_w * sym.var("bc"))(queue, bc=bc)

    from pytential.solve import gmres
    gmres_result = gmres(bound_op.scipy_op(queue, "sigma", dtype=np.float64),
                         bvp_rhs,
                         tol=1e-14,
                         progress=True,
                         stall_iterations=0,
                         hard_failure=True)

    sigma = bind(qbx,
                 sym.var("sigma") / sqrt_w)(queue, sigma=gmres_result.solution)

    # }}}

    from meshmode.discretization.visualization import make_visualizer
    bdry_vis = make_visualizer(queue, density_discr, 20)
    bdry_vis.write_vtk_file("laplace.vtu", [
        ("sigma", sigma),
    ])

    # {{{ postprocess/visualize

    repr_kwargs = dict(qbx_forced_limit=None)
    representation_sym = (sym.S(kernel, inv_sqrt_w_sigma, **repr_kwargs) +
                          sym.D(kernel, inv_sqrt_w_sigma, **repr_kwargs))

    from sumpy.visualization import FieldPlotter
    fplot = FieldPlotter(np.zeros(3), extent=20, npoints=50)

    targets = cl.array.to_device(queue, fplot.points)

    qbx_stick_out = qbx.copy(target_stick_out_factor=0.2)

    try:
        fld_in_vol = bind((qbx_stick_out, PointsTarget(targets)),
                          representation_sym)(queue, sigma=sigma).get()
    except QBXTargetAssociationFailedException as e:
        fplot.write_vtk_file("failed-targets.vts",
                             [("failed", e.failed_target_flags.get(queue))])
        raise

    #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
    fplot.write_vtk_file("potential-laplace-3d.vts", [
        ("potential", fld_in_vol),
    ])
예제 #12
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def main():
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

    cl_ctx = cl.create_some_context()
    queue = cl.CommandQueue(cl_ctx)

    from meshmode.mesh.generation import ellipse, make_curve_mesh
    from functools import partial

    if 0:
        mesh = make_curve_mesh(
                partial(ellipse, 1),
                np.linspace(0, 1, nelements+1),
                mesh_order)
    else:
        base_mesh = make_curve_mesh(
                partial(ellipse, 1),
                np.linspace(0, 1, nelements+1),
                mesh_order)

        from meshmode.mesh.processing import affine_map, merge_disjoint_meshes
        nx = 2
        ny = 2
        dx = 2 / nx
        meshes = [
                affine_map(
                    base_mesh,
                    A=np.diag([dx*0.25, dx*0.25]),
                    b=np.array([dx*(ix-nx/2), dx*(iy-ny/2)]))
                for ix in range(nx)
                for iy in range(ny)]

        mesh = merge_disjoint_meshes(meshes, single_group=True)

        if 0:
            from meshmode.mesh.visualization import draw_curve
            draw_curve(mesh)
            import matplotlib.pyplot as plt
            plt.show()

    pre_density_discr = Discretization(
            cl_ctx, mesh,
            InterpolatoryQuadratureSimplexGroupFactory(bdry_quad_order))

    from pytential.qbx import (
            QBXLayerPotentialSource, QBXTargetAssociationFailedException)
    qbx, _ = QBXLayerPotentialSource(
            pre_density_discr, fine_order=bdry_ovsmp_quad_order, qbx_order=qbx_order,
            fmm_order=fmm_order
            ).with_refinement()
    density_discr = qbx.density_discr

    # {{{ describe bvp

    from sumpy.kernel import LaplaceKernel, HelmholtzKernel
    kernel = HelmholtzKernel(2)

    cse = sym.cse

    sigma_sym = sym.var("sigma")
    sqrt_w = sym.sqrt_jac_q_weight(2)
    inv_sqrt_w_sigma = cse(sigma_sym/sqrt_w)

    # Brakhage-Werner parameter
    alpha = 1j

    # -1 for interior Dirichlet
    # +1 for exterior Dirichlet
    loc_sign = +1

    bdry_op_sym = (-loc_sign*0.5*sigma_sym
            + sqrt_w*(
                alpha*sym.S(kernel, inv_sqrt_w_sigma, k=sym.var("k"),
                    qbx_forced_limit=+1)
                - sym.D(kernel, inv_sqrt_w_sigma, k=sym.var("k"),
                    qbx_forced_limit="avg")
                ))

    # }}}

    bound_op = bind(qbx, bdry_op_sym)

    # {{{ fix rhs and solve

    nodes = density_discr.nodes().with_queue(queue)
    k_vec = np.array([2, 1])
    k_vec = k * k_vec / la.norm(k_vec, 2)

    def u_incoming_func(x):
        return cl.clmath.exp(
                1j * (x[0] * k_vec[0] + x[1] * k_vec[1]))

    bc = -u_incoming_func(nodes)

    bvp_rhs = bind(qbx, sqrt_w*sym.var("bc"))(queue, bc=bc)

    from pytential.solve import gmres
    gmres_result = gmres(
            bound_op.scipy_op(queue, "sigma", dtype=np.complex128, k=k),
            bvp_rhs, tol=1e-8, progress=True,
            stall_iterations=0,
            hard_failure=True)

    # }}}

    # {{{ postprocess/visualize

    sigma = gmres_result.solution

    repr_kwargs = dict(k=sym.var("k"), qbx_forced_limit=None)
    representation_sym = (
            alpha*sym.S(kernel, inv_sqrt_w_sigma, **repr_kwargs)
            - sym.D(kernel, inv_sqrt_w_sigma, **repr_kwargs))

    from sumpy.visualization import FieldPlotter
    fplot = FieldPlotter(np.zeros(2), extent=5, npoints=500)

    targets = cl.array.to_device(queue, fplot.points)

    u_incoming = u_incoming_func(targets)

    qbx_stick_out = qbx.copy(target_association_tolerance=0.05)

    ones_density = density_discr.zeros(queue)
    ones_density.fill(1)
    indicator = bind(
            (qbx_stick_out, PointsTarget(targets)),
            sym.D(LaplaceKernel(2), sym.var("sigma"), qbx_forced_limit=None))(
            queue, sigma=ones_density).get()

    try:
        fld_in_vol = bind(
                (qbx_stick_out, PointsTarget(targets)),
                representation_sym)(queue, sigma=sigma, k=k).get()
    except QBXTargetAssociationFailedException as e:
        fplot.write_vtk_file(
                "failed-targets.vts",
                [
                    ("failed", e.failed_target_flags.get(queue))
                    ]
                )
        raise

    #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
    fplot.write_vtk_file(
            "potential-helm.vts",
            [
                ("potential", fld_in_vol),
                ("indicator", indicator),
                ("u_incoming", u_incoming.get()),
                ]
            )
예제 #13
0
def main():
    import logging
    logging.basicConfig(level=logging.INFO)

    cl_ctx = cl.create_some_context()
    queue = cl.CommandQueue(cl_ctx)

    from meshmode.mesh.generation import ellipse, make_curve_mesh
    from functools import partial

    mesh = make_curve_mesh(
                partial(ellipse, 2),
                np.linspace(0, 1, nelements+1),
                mesh_order)

    pre_density_discr = Discretization(
            cl_ctx, mesh,
            InterpolatoryQuadratureSimplexGroupFactory(bdry_quad_order))

    from pytential.qbx import (
            QBXLayerPotentialSource, QBXTargetAssociationFailedException)
    qbx, _ = QBXLayerPotentialSource(
            pre_density_discr, fine_order=bdry_ovsmp_quad_order, qbx_order=qbx_order,
            fmm_order=fmm_order,
            expansion_disks_in_tree_have_extent=True,
            ).with_refinement()
    density_discr = qbx.density_discr

    from pytential.symbolic.pde.cahn_hilliard import CahnHilliardOperator
    chop = CahnHilliardOperator(
            # FIXME: Constants?
            lambda1=1.5,
            lambda2=1.25,
            c=1)

    unk = chop.make_unknown("sigma")
    bound_op = bind(qbx, chop.operator(unk))

    # {{{ fix rhs and solve

    nodes = density_discr.nodes().with_queue(queue)

    def g(xvec):
        x, y = xvec
        return cl.clmath.atan2(y, x)

    bc = sym.make_obj_array([
        # FIXME: Realistic BC
        g(nodes),
        -g(nodes),
        ])

    from pytential.solve import gmres
    gmres_result = gmres(
            bound_op.scipy_op(queue, "sigma", dtype=np.complex128),
            bc, tol=1e-8, progress=True,
            stall_iterations=0,
            hard_failure=True)

    # }}}

    # {{{ postprocess/visualize

    sigma = gmres_result.solution

    from sumpy.visualization import FieldPlotter
    fplot = FieldPlotter(np.zeros(2), extent=5, npoints=500)

    targets = cl.array.to_device(queue, fplot.points)

    qbx_stick_out = qbx.copy(target_association_tolerance=0.05)

    indicator_qbx = qbx_stick_out.copy(qbx_order=2)

    from sumpy.kernel import LaplaceKernel
    ones_density = density_discr.zeros(queue)
    ones_density.fill(1)
    indicator = bind(
            (indicator_qbx, PointsTarget(targets)),
            sym.D(LaplaceKernel(2), sym.var("sigma")))(
            queue, sigma=ones_density).get()

    try:
        fld_in_vol = bind(
                (qbx_stick_out, PointsTarget(targets)),
                chop.representation(unk))(queue, sigma=sigma).get()
    except QBXTargetAssociationFailedException as e:
        fplot.write_vtk_file(
                "failed-targets.vts",
                [
                    ("failed", e.failed_target_flags.get(queue))
                    ]
                )
        raise

    #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
    fplot.write_vtk_file(
            "potential.vts",
            [
                ("potential", fld_in_vol),
                ("indicator", indicator),
                ]
            )
예제 #14
0
def run_test(cl_ctx, queue):

    q_order = 5
    qbx_order = q_order
    fmm_backend = "sumpy"
    mesh = get_ellipse_mesh(20, 40, mesh_order=5)
    a = 1
    b = 1 / 40

    if 0:
        from meshmode.mesh.visualization import draw_curve
        import matplotlib.pyplot as plt
        draw_curve(mesh)
        plt.axes().set_aspect('equal')
        plt.show()

    from pytential.qbx import QBXLayerPotentialSource
    from meshmode.discretization import Discretization
    from meshmode.discretization.poly_element import \
            InterpolatoryQuadratureSimplexGroupFactory

    pre_density_discr = Discretization(
        cl_ctx, mesh, InterpolatoryQuadratureSimplexGroupFactory(q_order))

    refiner_extra_kwargs = {
        # "_expansion_disturbance_tolerance": 0.05,
        "_scaled_max_curvature_threshold": 1,
        "maxiter": 10,
    }

    qbx, _ = QBXLayerPotentialSource(
        pre_density_discr,
        fine_order=4 * q_order,
        qbx_order=qbx_order,
        fmm_backend=fmm_backend,
        fmm_order=qbx_order + 5,
    ).with_refinement(**refiner_extra_kwargs)

    if 1:
        print("%d stage-1 elements after refinement" %
              qbx.density_discr.mesh.nelements)
        print("%d stage-2 elements after refinement" %
              qbx.stage2_density_discr.mesh.nelements)
        print("quad stage-2 elements have %d nodes" %
              qbx.quad_stage2_density_discr.groups[0].nunit_nodes)

    def reference_solu(rvec):
        # a harmonic function
        x, y = rvec
        return 2.1 * x * y + (x**2 - y**2) * 0.5 + x

    bvals = reference_solu(qbx.density_discr.nodes().with_queue(queue))

    from pytential.symbolic.pde.scalar import DirichletOperator
    from sumpy.kernel import LaplaceKernel
    from pytential import sym, bind
    op = DirichletOperator(LaplaceKernel(2), -1)

    bound_op = bind(qbx.copy(target_association_tolerance=0.5),
                    op.operator(sym.var('sigma')))
    rhs = bind(qbx.density_discr, op.prepare_rhs(sym.var("bc")))(queue,
                                                                 bc=bvals)

    from pytential.solve import gmres
    gmres_result = gmres(bound_op.scipy_op(queue, "sigma", dtype=np.float64),
                         rhs,
                         tol=1e-12,
                         progress=True,
                         hard_failure=True,
                         stall_iterations=50,
                         no_progress_factor=1.05)

    from sumpy.visualization import FieldPlotter
    from pytential.target import PointsTarget
    pltsize = b * 1.5
    fplot = FieldPlotter(np.array([-1 + pltsize * 0.5, 0]),
                         extent=pltsize * 1.05,
                         npoints=500)
    plt_targets = cl.array.to_device(queue, fplot.points)

    interior_pts = (fplot.points[0]**2 / a**2 +
                    fplot.points[1]**2 / b**2) < 0.99

    exact_vals = reference_solu(fplot.points)
    out_errs = []

    for assotol in [0.05]:

        qbx_stick_out = qbx.copy(target_association_tolerance=0.05)

        vol_solution = bind((qbx_stick_out, PointsTarget(plt_targets)),
                            op.representation(sym.var('sigma')))(
                                queue, sigma=gmres_result.solution).get()

        interior_error_linf = (
            np.linalg.norm(np.abs(vol_solution - exact_vals)[interior_pts],
                           ord=np.inf) /
            np.linalg.norm(exact_vals[interior_pts], ord=np.inf))

        interior_error_l2 = (np.linalg.norm(
            np.abs(vol_solution - exact_vals)[interior_pts], ord=2) /
                             np.linalg.norm(exact_vals[interior_pts], ord=2))

        print("\nassotol = %f" % assotol)
        print("L_inf Error = %e " % interior_error_linf)
        print("L_2 Error = %e " % interior_error_l2)

        out_errs.append(
            ("error-%f" % assotol, np.abs(vol_solution - exact_vals)))

    if 1:
        fplot.write_vtk_file("results.vts", out_errs)
예제 #15
0
def timing_run(nx, ny):
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

    cl_ctx = cl.create_some_context()
    queue = cl.CommandQueue(cl_ctx)

    mesh = make_mesh(nx=nx, ny=ny)

    density_discr = Discretization(
        cl_ctx, mesh,
        InterpolatoryQuadratureSimplexGroupFactory(bdry_quad_order))

    from pytential.qbx import (QBXLayerPotentialSource,
                               QBXTargetAssociationFailedException)
    qbx = QBXLayerPotentialSource(density_discr,
                                  fine_order=bdry_ovsmp_quad_order,
                                  qbx_order=qbx_order,
                                  fmm_order=fmm_order)

    # {{{ describe bvp

    from sumpy.kernel import HelmholtzKernel
    kernel = HelmholtzKernel(2)

    cse = sym.cse

    sigma_sym = sym.var("sigma")
    sqrt_w = sym.sqrt_jac_q_weight(2)
    inv_sqrt_w_sigma = cse(sigma_sym / sqrt_w)

    # Brakhage-Werner parameter
    alpha = 1j

    # -1 for interior Dirichlet
    # +1 for exterior Dirichlet
    loc_sign = +1

    bdry_op_sym = (-loc_sign * 0.5 * sigma_sym + sqrt_w *
                   (alpha * sym.S(kernel, inv_sqrt_w_sigma, k=sym.var("k")) -
                    sym.D(kernel, inv_sqrt_w_sigma, k=sym.var("k"))))

    # }}}

    bound_op = bind(qbx, bdry_op_sym)

    # {{{ fix rhs and solve

    mode_nr = 3
    nodes = density_discr.nodes().with_queue(queue)
    angle = cl.clmath.atan2(nodes[1], nodes[0])

    sigma = cl.clmath.cos(mode_nr * angle)

    # }}}

    # {{{ postprocess/visualize

    repr_kwargs = dict(k=sym.var("k"), qbx_forced_limit=+1)

    sym_op = sym.S(kernel, sym.var("sigma"), **repr_kwargs)
    bound_op = bind(qbx, sym_op)

    print("FMM WARM-UP RUN 1: %d elements" % mesh.nelements)
    bound_op(queue, sigma=sigma, k=k)
    print("FMM WARM-UP RUN 2: %d elements" % mesh.nelements)
    bound_op(queue, sigma=sigma, k=k)
    queue.finish()
    print("FMM TIMING RUN: %d elements" % mesh.nelements)

    from time import time
    t_start = time()

    bound_op(queue, sigma=sigma, k=k)
    queue.finish()
    elapsed = time() - t_start

    print("FMM TIMING RUN DONE: %d elements -> %g s" %
          (mesh.nelements, elapsed))

    return (mesh.nelements, elapsed)

    if 0:
        from sumpy.visualization import FieldPlotter
        fplot = FieldPlotter(np.zeros(2), extent=5, npoints=1500)

        targets = cl.array.to_device(queue, fplot.points)

        qbx_tgt_tol = qbx.copy(target_association_tolerance=0.05)

        indicator_qbx = qbx_tgt_tol.copy(fmm_level_to_order=lambda lev: 7,
                                         qbx_order=2)

        ones_density = density_discr.zeros(queue)
        ones_density.fill(1)
        indicator = bind((indicator_qbx, PointsTarget(targets)),
                         sym_op)(queue, sigma=ones_density).get()

        qbx_stick_out = qbx.copy(target_stick_out_factor=0.1)
        try:
            fld_in_vol = bind((qbx_stick_out, PointsTarget(targets)),
                              sym_op)(queue, sigma=sigma, k=k).get()
        except QBXTargetAssociationFailedException as e:
            fplot.write_vtk_file(
                "failed-targets.vts",
                [("failed", e.failed_target_flags.get(queue))])
            raise

        #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
        fplot.write_vtk_file("potential-scaling.vts",
                             [("potential", fld_in_vol),
                              ("indicator", indicator)])
예제 #16
0
def main():
    # cl.array.to_device(queue, numpy_array)
    from meshmode.mesh.io import generate_gmsh, FileSource
    mesh = generate_gmsh(
            FileSource("ellipsoid.step"), 2, order=2,
            other_options=["-string", "Mesh.CharacteristicLengthMax = %g;" % h])

    from meshmode.mesh.processing import perform_flips
    # Flip elements--gmsh generates inside-out geometry.
    mesh = perform_flips(mesh, np.ones(mesh.nelements))

    print("%d elements" % mesh.nelements)

    from meshmode.mesh.processing import find_bounding_box
    bbox_min, bbox_max = find_bounding_box(mesh)
    bbox_center = 0.5*(bbox_min+bbox_max)
    bbox_size = max(bbox_max-bbox_min) / 2

    logger.info("%d elements" % mesh.nelements)

    from pytential.qbx import QBXLayerPotentialSource
    from meshmode.discretization import Discretization
    from meshmode.discretization.poly_element import \
            InterpolatoryQuadratureSimplexGroupFactory

    density_discr = Discretization(
            cl_ctx, mesh, InterpolatoryQuadratureSimplexGroupFactory(target_order))

    qbx = QBXLayerPotentialSource(density_discr, 4*target_order, qbx_order,
            fmm_order=qbx_order + 10, fmm_backend="fmmlib")

    from pytential.symbolic.pde.maxwell import MuellerAugmentedMFIEOperator
    pde_op = MuellerAugmentedMFIEOperator(
            omega=0.4,
            epss=[1.4, 1.0],
            mus=[1.2, 1.0],
            )
    from pytential import bind, sym

    unk = pde_op.make_unknown("sigma")
    sym_operator = pde_op.operator(unk)
    sym_rhs = pde_op.rhs(
            sym.make_sym_vector("Einc", 3),
            sym.make_sym_vector("Hinc", 3))
    sym_repr = pde_op.representation(0, unk)

    if 1:
        expr = sym_repr
        print(sym.pretty(expr))

        print("#"*80)
        from pytential.target import PointsTarget

        tgt_points=np.zeros((3,1))
        tgt_points[0,0] = 100
        tgt_points[1,0] = -200
        tgt_points[2,0] = 300

        bound_op = bind((qbx, PointsTarget(tgt_points)), expr)
        print(bound_op.code)

    if 1:

        def green3e(x,y,z,source,strength,k):
        # electric field corresponding to dyadic green's function
        # due to monochromatic electric dipole located at "source".
        # "strength" is the the intensity of the dipole.
        #  E = (I + Hess)(exp(ikr)/r) dot (strength)
        #
            dx = x - source[0]
            dy = y - source[1]
            dz = z - source[2]
            rr = np.sqrt(dx**2 + dy**2 + dz**2)

            fout = np.exp(1j*k*rr)/rr
            evec = fout*strength
            qmat = np.zeros((3,3),dtype=np.complex128)

            qmat[0,0]=(2*dx**2-dy**2-dz**2)*(1-1j*k*rr)
            qmat[1,1]=(2*dy**2-dz**2-dx**2)*(1-1j*k*rr)
            qmat[2,2]=(2*dz**2-dx**2-dy**2)*(1-1j*k*rr)

            qmat[0,0]=qmat[0,0]+(-k**2*dx**2*rr**2)
            qmat[1,1]=qmat[1,1]+(-k**2*dy**2*rr**2)
            qmat[2,2]=qmat[2,2]+(-k**2*dz**2*rr**2)

            qmat[0,1]=(3-k**2*rr**2-3*1j*k*rr)*(dx*dy)
            qmat[1,2]=(3-k**2*rr**2-3*1j*k*rr)*(dy*dz)
            qmat[2,0]=(3-k**2*rr**2-3*1j*k*rr)*(dz*dx)

            qmat[1,0]=qmat[0,1]
            qmat[2,1]=qmat[1,2]
            qmat[0,2]=qmat[2,0]

            fout=np.exp(1j*k*rr)/rr**5/k**2

            fvec = fout*np.dot(qmat,strength)
            evec = evec + fvec
            return evec

        def green3m(x,y,z,source,strength,k):
        # magnetic field corresponding to dyadic green's function
        # due to monochromatic electric dipole located at "source".
        # "strength" is the the intensity of the dipole.
        #  H = curl((I + Hess)(exp(ikr)/r) dot (strength)) = 
        #  strength \cross \grad (exp(ikr)/r)
        #
            dx = x - source[0]
            dy = y - source[1]
            dz = z - source[2]
            rr = np.sqrt(dx**2 + dy**2 + dz**2)

            fout=(1-1j*k*rr)*np.exp(1j*k*rr)/rr**3
            fvec = np.zeros(3,dtype=np.complex128)
            fvec[0] = fout*dx
            fvec[1] = fout*dy
            fvec[2] = fout*dz

            hvec = np.cross(strength,fvec)

            return hvec

        def dipole3e(x,y,z,source,strength,k):
        #
        #  evalaute electric and magnetic field due
        #  to monochromatic electric dipole located at "source"
        #  with intensity "strength"

            evec = green3e(x,y,z,source,strength,k)
            evec = evec*1j*k
            hvec = green3m(x,y,z,source,strength,k)
            return evec,hvec
            
        def dipole3m(x,y,z,source,strength,k):
        #
        #  evalaute electric and magnetic field due
        #  to monochromatic magnetic dipole located at "source"
        #  with intensity "strength"
            evec = green3m(x,y,z,source,strength,k)
            hvec = green3e(x,y,z,source,strength,k)
            hvec = -hvec*1j*k
            return evec,hvec
            

        def dipole3eall(x,y,z,sources,strengths,k):
            ns = len(strengths)
            evec = np.zeros(3,dtype=np.complex128)
            hvec = np.zeros(3,dtype=np.complex128)

            for i in range(ns):
                evect,hvect = dipole3e(x,y,z,sources[i],strengths[i],k)
                evec = evec + evect
                hvec = hvec + hvect

        nodes = density_discr.nodes().with_queue(queue).get()
        source = [0.01,-0.03,0.02]
#        source = cl.array.to_device(queue,np.zeros(3))
#        source[0] = 0.01
#        source[1] =-0.03
#        source[2] = 0.02
        strength = np.ones(3)
       
#        evec = cl.array.to_device(queue,np.zeros((3,len(nodes[0])),dtype=np.complex128))
#        hvec = cl.array.to_device(queue,np.zeros((3,len(nodes[0])),dtype=np.complex128))

        evec = np.zeros((3,len(nodes[0])),dtype=np.complex128)
        hvec = np.zeros((3,len(nodes[0])),dtype=np.complex128)
        for i in range(len(nodes[0])):
            evec[:,i],hvec[:,i] = dipole3e(nodes[0][i],nodes[1][i],nodes[2][i],source,strength,k)
        print(np.shape(hvec))
        print(type(evec))
        print(type(hvec))

        evec = cl.array.to_device(queue,evec)
        hvec = cl.array.to_device(queue,hvec)

        bvp_rhs = bind(qbx, sym_rhs)(queue,Einc=evec,Hinc=hvec)
        print(np.shape(bvp_rhs))
        print(type(bvp_rhs))
#        print(bvp_rhs)
        1/-1

        bound_op = bind(qbx, sym_operator)

        from pytential.solve import gmres
        if 0:
            gmres_result = gmres(
                bound_op.scipy_op(queue, "sigma", dtype=np.complex128, k=k),
                bvp_rhs, tol=1e-8, progress=True,
                stall_iterations=0,
                hard_failure=True)

            sigma = gmres_result.solution

        fld_at_tgt = bind((qbx, PointsTarget(tgt_points)), sym_repr)(queue,
        sigma=bvp_rhs,k=k)
        fld_at_tgt = np.array([
            fi.get() for fi in fld_at_tgt
            ])
        print(fld_at_tgt)
        1/0

    # }}}

    #mlab.figure(bgcolor=(1, 1, 1))
    if 1:
        from meshmode.discretization.visualization import make_visualizer
        bdry_vis = make_visualizer(queue, density_discr, target_order)

        bdry_normals = bind(density_discr, sym.normal(3))(queue)\
                .as_vector(dtype=object)

        bdry_vis.write_vtk_file("source.vtu", [
            ("sigma", sigma),
            ("bdry_normals", bdry_normals),
            ])

        fplot = FieldPlotter(bbox_center, extent=2*bbox_size, npoints=(150, 150, 1))

        qbx_tgt_tol = qbx.copy(target_association_tolerance=0.1)
        from pytential.target import PointsTarget
        from pytential.qbx import QBXTargetAssociationFailedException

        rho_sym = sym.var("rho")

        try:
            fld_in_vol = bind(
                    (qbx_tgt_tol, PointsTarget(fplot.points)),
                    sym.make_obj_array([
                        sym.S(pde_op.kernel, rho_sym, k=sym.var("k"),
                            qbx_forced_limit=None),
                        sym.d_dx(3, sym.S(pde_op.kernel, rho_sym, k=sym.var("k"),
                            qbx_forced_limit=None)),
                        sym.d_dy(3, sym.S(pde_op.kernel, rho_sym, k=sym.var("k"),
                            qbx_forced_limit=None)),
                        sym.d_dz(3, sym.S(pde_op.kernel, rho_sym, k=sym.var("k"),
                            qbx_forced_limit=None)),
                        ])
                    )(queue, jt=jt, rho=rho, k=k)
        except QBXTargetAssociationFailedException as e:
            fplot.write_vtk_file(
                    "failed-targets.vts",
                    [
                        ("failed_targets", e.failed_target_flags.get(queue))
                        ])
            raise

        fld_in_vol = sym.make_obj_array(
            [fiv.get() for fiv in fld_in_vol])

        #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
        fplot.write_vtk_file(
                "potential.vts",
                [
                    ("potential", fld_in_vol[0]),
                    ("grad", fld_in_vol[1:]),
                    ]
                )
예제 #17
0
def main():
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

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

    target_order = 16
    qbx_order = 3
    nelements = 60
    mode_nr = 0

    k = 0
    if k:
        kernel = HelmholtzKernel(2)
    else:
        kernel = LaplaceKernel(2)

    mesh = make_curve_mesh(
        #lambda t: ellipse(1, t),
        starfish,
        np.linspace(0, 1, nelements + 1),
        target_order)

    from pytential.qbx import QBXLayerPotentialSource
    from meshmode.discretization import Discretization
    from meshmode.discretization.poly_element import \
            InterpolatoryQuadratureSimplexGroupFactory

    pre_density_discr = Discretization(
        actx, mesh, InterpolatoryQuadratureSimplexGroupFactory(target_order))

    unaccel_qbx = QBXLayerPotentialSource(
        pre_density_discr,
        fine_order=2 * target_order,
        qbx_order=qbx_order,
        fmm_order=False,
        target_association_tolerance=.05,
    )

    from pytential.target import PointsTarget
    fplot = FieldPlotter(np.zeros(2), extent=5, npoints=600)

    from pytential import GeometryCollection
    places = GeometryCollection({
        "unaccel_qbx": unaccel_qbx,
        "qbx": unaccel_qbx.copy(fmm_order=10),
        "targets": PointsTarget(fplot.points)
    })
    density_discr = places.get_discretization("unaccel_qbx")

    nodes = thaw(actx, density_discr.nodes())
    angle = actx.np.arctan2(nodes[1], nodes[0])

    from pytential import bind, sym
    if k:
        kernel_kwargs = {"k": sym.var("k")}
    else:
        kernel_kwargs = {}

    def get_op():
        kwargs = dict(qbx_forced_limit=None)
        kwargs.update(kernel_kwargs)
        # return sym.d_dx(2, sym.S(kernel, sym.var("sigma"), **kwargs))
        # return sym.D(kernel, sym.var("sigma"), **kwargs)
        return sym.S(kernel, sym.var("sigma"), **kwargs)

    op = get_op()

    sigma = actx.np.cos(mode_nr * angle)

    if isinstance(kernel, HelmholtzKernel):
        for i, elem in np.ndenumerate(sigma):
            sigma[i] = elem.astype(np.complex128)

    fld_in_vol = bind(places, op,
                      auto_where=("unaccel_qbx", "targets"))(actx,
                                                             sigma=sigma,
                                                             k=k).get()

    fmm_fld_in_vol = bind(places, op,
                          auto_where=("qbx", "targets"))(actx,
                                                         sigma=sigma,
                                                         k=k).get()

    err = fmm_fld_in_vol - fld_in_vol

    try:
        import matplotlib
    except ImportError:
        return

    matplotlib.use("Agg")
    im = fplot.show_scalar_in_matplotlib(np.log10(np.abs(err) + 1e-17))

    from matplotlib.colors import Normalize
    im.set_norm(Normalize(vmin=-12, vmax=0))

    import matplotlib.pyplot as pt
    from matplotlib.ticker import NullFormatter
    pt.gca().xaxis.set_major_formatter(NullFormatter())
    pt.gca().yaxis.set_major_formatter(NullFormatter())

    cb = pt.colorbar(shrink=0.9)
    cb.set_label(r"$\log_{10}(\mathrm{Error})$")

    pt.savefig("fmm-error-order-%d.pdf" % qbx_order)
def test_target_specific_qbx(actx_factory, op, helmholtz_k, qbx_order):
    logging.basicConfig(level=logging.INFO)

    actx = actx_factory()

    target_order = 4
    fmm_tol = 1e-3

    from meshmode.mesh.generation import generate_sphere
    mesh = generate_sphere(1, target_order)

    from meshmode.discretization import Discretization
    from meshmode.discretization.poly_element import \
        InterpolatoryQuadratureSimplexGroupFactory
    from pytential.qbx import QBXLayerPotentialSource
    pre_density_discr = Discretization(
        actx, mesh, InterpolatoryQuadratureSimplexGroupFactory(target_order))

    from sumpy.expansion.level_to_order import SimpleExpansionOrderFinder
    qbx = QBXLayerPotentialSource(
        pre_density_discr,
        4 * target_order,
        qbx_order=qbx_order,
        fmm_level_to_order=SimpleExpansionOrderFinder(fmm_tol),
        fmm_backend="fmmlib",
        _expansions_in_tree_have_extent=True,
        _expansion_stick_out_factor=0.9,
        _use_target_specific_qbx=False,
    )

    kernel_length_scale = 5 / abs(helmholtz_k) if helmholtz_k else None
    places = {
        "qbx": qbx,
        "qbx_target_specific": qbx.copy(_use_target_specific_qbx=True)
    }

    from pytential.qbx.refinement import refine_geometry_collection
    places = GeometryCollection(places, auto_where="qbx")
    places = refine_geometry_collection(
        places, kernel_length_scale=kernel_length_scale)

    density_discr = places.get_discretization("qbx")
    nodes = thaw(density_discr.nodes(), actx)
    u_dev = actx.np.sin(nodes[0])

    if helmholtz_k == 0:
        kernel = LaplaceKernel(3)
        kernel_kwargs = {}
    else:
        kernel = HelmholtzKernel(3, allow_evanescent=True)
        kernel_kwargs = {"k": sym.var("k")}

    u_sym = sym.var("u")

    if op == "S":
        op = sym.S
    elif op == "D":
        op = sym.D
    elif op == "Sp":
        op = sym.Sp
    else:
        raise ValueError("unknown operator: '%s'" % op)

    expr = op(kernel, u_sym, qbx_forced_limit=-1, **kernel_kwargs)

    bound_op = bind(places, expr)
    pot_ref = actx.to_numpy(
        flatten(bound_op(actx, u=u_dev, k=helmholtz_k), actx))

    bound_op = bind(places, expr, auto_where="qbx_target_specific")
    pot_tsqbx = actx.to_numpy(
        flatten(bound_op(actx, u=u_dev, k=helmholtz_k), actx))

    assert np.allclose(pot_tsqbx, pot_ref, atol=1e-13, rtol=1e-13)
예제 #19
0
def timing_run(nx, ny):
    import logging
    logging.basicConfig(level=logging.WARNING)  # INFO for more progress info

    cl_ctx = cl.create_some_context()
    queue = cl.CommandQueue(cl_ctx)

    mesh = make_mesh(nx=nx, ny=ny)

    density_discr = Discretization(
            cl_ctx, mesh,
            InterpolatoryQuadratureSimplexGroupFactory(bdry_quad_order))

    from pytential.qbx import (
            QBXLayerPotentialSource, QBXTargetAssociationFailedException)
    qbx = QBXLayerPotentialSource(
            density_discr, fine_order=bdry_ovsmp_quad_order, qbx_order=qbx_order,
            fmm_order=fmm_order
            )

    # {{{ describe bvp

    from sumpy.kernel import HelmholtzKernel
    kernel = HelmholtzKernel(2)

    cse = sym.cse

    sigma_sym = sym.var("sigma")
    sqrt_w = sym.sqrt_jac_q_weight(2)
    inv_sqrt_w_sigma = cse(sigma_sym/sqrt_w)

    # Brakhage-Werner parameter
    alpha = 1j

    # -1 for interior Dirichlet
    # +1 for exterior Dirichlet
    loc_sign = +1

    bdry_op_sym = (-loc_sign*0.5*sigma_sym
            + sqrt_w*(
                alpha*sym.S(kernel, inv_sqrt_w_sigma, k=sym.var("k"))
                - sym.D(kernel, inv_sqrt_w_sigma, k=sym.var("k"))
                ))

    # }}}

    bound_op = bind(qbx, bdry_op_sym)

    # {{{ fix rhs and solve

    mode_nr = 3
    nodes = density_discr.nodes().with_queue(queue)
    angle = cl.clmath.atan2(nodes[1], nodes[0])

    sigma = cl.clmath.cos(mode_nr*angle)

    # }}}

    # {{{ postprocess/visualize

    repr_kwargs = dict(k=sym.var("k"), qbx_forced_limit=+1)

    sym_op = sym.S(kernel, sym.var("sigma"), **repr_kwargs)
    bound_op = bind(qbx, sym_op)

    print("FMM WARM-UP RUN 1: %d elements" % mesh.nelements)
    bound_op(queue, sigma=sigma, k=k)
    print("FMM WARM-UP RUN 2: %d elements" % mesh.nelements)
    bound_op(queue, sigma=sigma, k=k)
    queue.finish()
    print("FMM TIMING RUN: %d elements" % mesh.nelements)

    from time import time
    t_start = time()

    bound_op(queue, sigma=sigma, k=k)
    queue.finish()
    elapsed = time()-t_start

    print("FMM TIMING RUN DONE: %d elements -> %g s"
            % (mesh.nelements, elapsed))

    return (mesh.nelements, elapsed)

    if 0:
        from sumpy.visualization import FieldPlotter
        fplot = FieldPlotter(np.zeros(2), extent=5, npoints=1500)

        targets = cl.array.to_device(queue, fplot.points)

        qbx_tgt_tol = qbx.copy(target_association_tolerance=0.05)

        indicator_qbx = qbx_tgt_tol.copy(
                fmm_level_to_order=lambda lev: 7, qbx_order=2)

        ones_density = density_discr.zeros(queue)
        ones_density.fill(1)
        indicator = bind(
                (indicator_qbx, PointsTarget(targets)),
                sym_op)(
                queue, sigma=ones_density).get()

        qbx_stick_out = qbx.copy(target_stick_out_factor=0.1)
        try:
            fld_in_vol = bind(
                    (qbx_stick_out, PointsTarget(targets)),
                    sym_op)(queue, sigma=sigma, k=k).get()
        except QBXTargetAssociationFailedException as e:
            fplot.write_vtk_file(
                    "failed-targets.vts",
                    [
                        ("failed", e.failed_target_flags.get(queue))
                        ]
                    )
            raise

        #fplot.show_scalar_in_mayavi(fld_in_vol.real, max_val=5)
        fplot.write_vtk_file(
                "potential-scaling.vts",
                [
                    ("potential", fld_in_vol),
                    ("indicator", indicator)
                    ]
                )
예제 #20
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                ("rho", rho),
                ("Einc", inc_field_scat.e),
                ("Hinc", inc_field_scat.h),
                ("bdry_normals", bdry_normals),
                ("e_bc_residual", eh_bc_values[:3]),
                ("h_bc_residual", eh_bc_values[3]),
            ])

            fplot = make_field_plotter_from_bbox(find_bounding_box(
                scat_discr.mesh),
                                                 h=(0.05, 0.05, 0.3),
                                                 extend_factor=0.3)

            from pytential.qbx import QBXTargetAssociationFailedException

            qbx_tgt_tol = qbx.copy(target_association_tolerance=0.2)

            fplot_tgt = PointsTarget(cl.array.to_device(queue, fplot.points))
            try:
                fplot_repr = eval_repr_at(fplot_tgt, source=qbx_tgt_tol)
            except QBXTargetAssociationFailedException as e:
                fplot.write_vtk_file(
                    "failed-targets.vts",
                    [("failed_targets", e.failed_target_flags.get(queue))])
                raise

            fplot_repr = EHField(vector_from_device(queue, fplot_repr))

            fplot_inc = EHField(
                vector_from_device(queue, eval_inc_field_at(fplot_tgt)))
예제 #21
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def test_pec_mfie_extinction(ctx_getter, case, visualize=False):
    """For (say) is_interior=False (the 'exterior' MFIE), this test verifies
    extinction of the combined (incoming + scattered) field on the interior
    of the scatterer.
    """
    logging.basicConfig(level=logging.INFO)

    cl_ctx = ctx_getter()
    queue = cl.CommandQueue(cl_ctx)

    np.random.seed(12)

    knl_kwargs = {"k": case.k}

    # {{{ come up with a solution to Maxwell's equations

    j_sym = sym.make_sym_vector("j", 3)
    jt_sym = sym.make_sym_vector("jt", 2)
    rho_sym = sym.var("rho")

    from pytential.symbolic.pde.maxwell import (
            PECChargeCurrentMFIEOperator,
            get_sym_maxwell_point_source,
            get_sym_maxwell_plane_wave)
    mfie = PECChargeCurrentMFIEOperator()

    test_source = case.get_source(queue)

    calc_patch = CalculusPatch(np.array([-3, 0, 0]), h=0.01)
    calc_patch_tgt = PointsTarget(cl.array.to_device(queue, calc_patch.points))

    rng = cl.clrandom.PhiloxGenerator(cl_ctx, seed=12)
    src_j = rng.normal(queue, (3, test_source.nnodes), dtype=np.float64)

    def eval_inc_field_at(tgt):
        if 0:
            # plane wave
            return bind(
                    tgt,
                    get_sym_maxwell_plane_wave(
                        amplitude_vec=np.array([1, 1, 1]),
                        v=np.array([1, 0, 0]),
                        omega=case.k)
                    )(queue)
        else:
            # point source
            return bind(
                    (test_source, tgt),
                    get_sym_maxwell_point_source(mfie.kernel, j_sym, mfie.k)
                    )(queue, j=src_j, k=case.k)

    pde_test_inc = EHField(
            vector_from_device(queue, eval_inc_field_at(calc_patch_tgt)))

    source_maxwell_resids = [
            calc_patch.norm(x, np.inf) / calc_patch.norm(pde_test_inc.e, np.inf)
            for x in frequency_domain_maxwell(
                calc_patch, pde_test_inc.e, pde_test_inc.h, case.k)]
    print("Source Maxwell residuals:", source_maxwell_resids)
    assert max(source_maxwell_resids) < 1e-6

    # }}}

    loc_sign = -1 if case.is_interior else +1

    from pytools.convergence import EOCRecorder

    eoc_rec_repr_maxwell = EOCRecorder()
    eoc_pec_bc = EOCRecorder()
    eoc_rec_e = EOCRecorder()
    eoc_rec_h = EOCRecorder()

    from pytential.qbx import QBXLayerPotentialSource
    from meshmode.discretization import Discretization
    from meshmode.discretization.poly_element import \
            InterpolatoryQuadratureSimplexGroupFactory
    from sumpy.expansion.level_to_order import SimpleExpansionOrderFinder

    for resolution in case.resolutions:
        scat_mesh = case.get_mesh(resolution, case.target_order)
        observation_mesh = case.get_observation_mesh(case.target_order)

        pre_scat_discr = Discretization(
                cl_ctx, scat_mesh,
                InterpolatoryQuadratureSimplexGroupFactory(case.target_order))
        qbx, _ = QBXLayerPotentialSource(
                pre_scat_discr, fine_order=4*case.target_order,
                qbx_order=case.qbx_order,
                fmm_level_to_order=SimpleExpansionOrderFinder(
                    case.fmm_tolerance),
                fmm_backend=case.fmm_backend
                ).with_refinement(_expansion_disturbance_tolerance=0.05)
        h_max = qbx.h_max

        scat_discr = qbx.density_discr
        obs_discr = Discretization(
                cl_ctx, observation_mesh,
                InterpolatoryQuadratureSimplexGroupFactory(case.target_order))

        inc_field_scat = EHField(eval_inc_field_at(scat_discr))
        inc_field_obs = EHField(eval_inc_field_at(obs_discr))

        # {{{ system solve

        inc_xyz_sym = EHField(sym.make_sym_vector("inc_fld", 6))

        bound_j_op = bind(qbx, mfie.j_operator(loc_sign, jt_sym))
        j_rhs = bind(qbx, mfie.j_rhs(inc_xyz_sym.h))(
                queue, inc_fld=inc_field_scat.field, **knl_kwargs)

        gmres_settings = dict(
                tol=case.gmres_tol,
                progress=True,
                hard_failure=True,
                stall_iterations=50, no_progress_factor=1.05)
        from pytential.solve import gmres
        gmres_result = gmres(
                bound_j_op.scipy_op(queue, "jt", np.complex128, **knl_kwargs),
                j_rhs, **gmres_settings)

        jt = gmres_result.solution

        bound_rho_op = bind(qbx, mfie.rho_operator(loc_sign, rho_sym))
        rho_rhs = bind(qbx, mfie.rho_rhs(jt_sym, inc_xyz_sym.e))(
                queue, jt=jt, inc_fld=inc_field_scat.field, **knl_kwargs)

        gmres_result = gmres(
                bound_rho_op.scipy_op(queue, "rho", np.complex128, **knl_kwargs),
                rho_rhs, **gmres_settings)

        rho = gmres_result.solution

        # }}}

        jxyz = bind(qbx, sym.tangential_to_xyz(jt_sym))(queue, jt=jt)

        # {{{ volume eval

        sym_repr = mfie.scattered_volume_field(jt_sym, rho_sym)

        def eval_repr_at(tgt, source=None):
            if source is None:
                source = qbx

            return bind((source, tgt), sym_repr)(queue, jt=jt, rho=rho, **knl_kwargs)

        pde_test_repr = EHField(
                vector_from_device(queue, eval_repr_at(calc_patch_tgt)))

        maxwell_residuals = [
                calc_patch.norm(x, np.inf) / calc_patch.norm(pde_test_repr.e, np.inf)
                for x in frequency_domain_maxwell(
                    calc_patch, pde_test_repr.e, pde_test_repr.h, case.k)]
        print("Maxwell residuals:", maxwell_residuals)

        eoc_rec_repr_maxwell.add_data_point(h_max, max(maxwell_residuals))

        # }}}

        # {{{ check PEC BC on total field

        bc_repr = EHField(mfie.scattered_volume_field(
            jt_sym, rho_sym, qbx_forced_limit=loc_sign))
        pec_bc_e = sym.n_cross(bc_repr.e + inc_xyz_sym.e)
        pec_bc_h = sym.normal(3).as_vector().dot(bc_repr.h + inc_xyz_sym.h)

        eh_bc_values = bind(qbx, sym.join_fields(pec_bc_e, pec_bc_h))(
                    queue, jt=jt, rho=rho, inc_fld=inc_field_scat.field,
                    **knl_kwargs)

        def scat_norm(f):
            return norm(qbx, queue, f, p=np.inf)

        e_bc_residual = scat_norm(eh_bc_values[:3]) / scat_norm(inc_field_scat.e)
        h_bc_residual = scat_norm(eh_bc_values[3]) / scat_norm(inc_field_scat.h)

        print("E/H PEC BC residuals:", h_max, e_bc_residual, h_bc_residual)

        eoc_pec_bc.add_data_point(h_max, max(e_bc_residual, h_bc_residual))

        # }}}

        # {{{ visualization

        if visualize:
            from meshmode.discretization.visualization import make_visualizer
            bdry_vis = make_visualizer(queue, scat_discr, case.target_order+3)

            bdry_normals = bind(scat_discr, sym.normal(3))(queue)\
                    .as_vector(dtype=object)

            bdry_vis.write_vtk_file("source-%s.vtu" % resolution, [
                ("j", jxyz),
                ("rho", rho),
                ("Einc", inc_field_scat.e),
                ("Hinc", inc_field_scat.h),
                ("bdry_normals", bdry_normals),
                ("e_bc_residual", eh_bc_values[:3]),
                ("h_bc_residual", eh_bc_values[3]),
                ])

            fplot = make_field_plotter_from_bbox(
                    find_bounding_box(scat_discr.mesh), h=(0.05, 0.05, 0.3),
                    extend_factor=0.3)

            from pytential.qbx import QBXTargetAssociationFailedException

            qbx_tgt_tol = qbx.copy(target_association_tolerance=0.2)

            fplot_tgt = PointsTarget(cl.array.to_device(queue, fplot.points))
            try:
                fplot_repr = eval_repr_at(fplot_tgt, source=qbx_tgt_tol)
            except QBXTargetAssociationFailedException as e:
                fplot.write_vtk_file(
                        "failed-targets.vts",
                        [
                            ("failed_targets", e.failed_target_flags.get(queue))
                            ])
                raise

            fplot_repr = EHField(vector_from_device(queue, fplot_repr))

            fplot_inc = EHField(
                    vector_from_device(queue, eval_inc_field_at(fplot_tgt)))

            fplot.write_vtk_file(
                    "potential-%s.vts" % resolution,
                    [
                        ("E", fplot_repr.e),
                        ("H", fplot_repr.h),
                        ("Einc", fplot_inc.e),
                        ("Hinc", fplot_inc.h),
                        ]
                    )

        # }}}

        # {{{ error in E, H

        obs_repr = EHField(eval_repr_at(obs_discr))

        def obs_norm(f):
            return norm(obs_discr, queue, f, p=np.inf)

        rel_err_e = (obs_norm(inc_field_obs.e + obs_repr.e)
                / obs_norm(inc_field_obs.e))
        rel_err_h = (obs_norm(inc_field_obs.h + obs_repr.h)
                / obs_norm(inc_field_obs.h))

        # }}}

        print("ERR", h_max, rel_err_h, rel_err_e)

        eoc_rec_h.add_data_point(h_max, rel_err_h)
        eoc_rec_e.add_data_point(h_max, rel_err_e)

    print("--------------------------------------------------------")
    print("is_interior=%s" % case.is_interior)
    print("--------------------------------------------------------")

    good = True
    for which_eoc, eoc_rec, order_tol in [
            ("maxwell", eoc_rec_repr_maxwell, 1.5),
            ("PEC BC", eoc_pec_bc, 1.5),
            ("H", eoc_rec_h, 1.5),
            ("E", eoc_rec_e, 1.5)]:
        print(which_eoc)
        print(eoc_rec.pretty_print())

        if len(eoc_rec.history) > 1:
            if eoc_rec.order_estimate() < case.qbx_order - order_tol:
                good = False

    assert good