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How to use is_periodic method in localstack

Best Python code snippet using localstack_python

trajectory.py

Source:trajectory.py

1import numpy as np2from scipy.interpolate import UnivariateSpline3from wzk.math2 import angle2minuspi_pluspi4def full2inner(x):5    return x[..., 1:-1, :].copy()6def inner2full(inner, start=None, end=None):7    n_samples = inner.shape[0]8    def __repeat(x):9        x = np.atleast_2d(x)10        if inner.ndim != 3:11            return x12        else:13            if x.ndim == 2:14                x = x[:, np.newaxis, :]15            return x.repeat(n_samples // x.shape[0], axis=0)16    if start is not None:17        start = __repeat(start)18        inner = np.concatenate((start, inner), axis=-2)19    if end is not None:20        end = __repeat(end)21        inner = np.concatenate((inner, end), axis=-2)22    return inner23def full2start_end(x, mode=''):24    if mode == '1':25        return x[..., [0, -1], :].copy()26    if mode == '20':27        return x[..., 0, :].copy(), x[..., -1, :].copy()28    elif mode == '21':29        return x[..., :1, :].copy(), x[..., -1:, :].copy()30    else:31        raise NotImplementedError32def path_mode(x, mode=None):33    if mode is None or mode == 'full':34        return x35    elif mode == 'inner':36        return x[..., 1:-1, :]37    elif mode == 'wo_start':38        return x[..., 1:, :]39    elif mode == 'wo_end':40        return x[..., :-1, :]41    else:42        raise ValueError43def flat2full(flat, n_dof):44    if flat.ndim == 1:45        flat = flat.reshape(-1, n_dof)46    elif flat.ndim == 2:47        flat = flat.reshape(len(flat), -1, n_dof)48    return flat49def full2flat(x):50    if x.ndim == 2:51        x = x.reshape(-1)52    elif x.ndim == 3:53        x = x.reshape(len(x), -1)54    return x55def periodic_dof_wrapper(x,56                         is_periodic=None):57    if is_periodic is not None and any(is_periodic):58        x[..., is_periodic] = angle2minuspi_pluspi(x[..., is_periodic])59    return x60def get_steps(q,61              is_periodic=None):62    return periodic_dof_wrapper(np.diff(q, axis=-2), is_periodic=is_periodic)63def get_steps_norm(q,64                   is_periodic=None):65    return np.linalg.norm(get_steps(q=q, is_periodic=is_periodic), axis=-1)66def get_substeps(x, n,67                 is_periodic=None, include_start=True):68    *shape, m, d = x.shape69    # only fill in substeps if the number is greater 1,70    if n <= 1 or m <= 1:71        if include_start:72            return x73        else:  # How often does this happen? once?: fill_linear_connection74            return x[..., 1:, :]75    steps = get_steps(q=x, is_periodic=is_periodic)76    delta = (np.arange(n-1, -1, -1)/n) * steps[..., np.newaxis]77    x_ss = x[..., 1:, :, np.newaxis] - delta78    x_ss = np.swapaxes(x_ss, -2, -1)79    x_ss = x_ss.reshape(shape + [(m-1) * n, d])80    if include_start:81        x_ss = np.concatenate((x[..., :1, :], x_ss), axis=-2)82    x_ss = periodic_dof_wrapper(x_ss, is_periodic=is_periodic)83    return x_ss84def get_steps_between(start, end, n, is_periodic=None):85    q = np.concatenate((start[..., np.newaxis, :], end[..., np.newaxis, :]), axis=-2)86    q = get_substeps(q, n=n-1, is_periodic=is_periodic)87    return q88def get_substeps_adjusted(x, n,89                          is_periodic=None, weighting=None):90    *shape, m, d = x.shape91    if shape:92        shape = tuple(shape)93        x_n = np.zeros(shape+(n, d))94        for i in np.ndindex(*shape):95            x_n[i] = get_substeps_adjusted(x=x[i], n=n, is_periodic=is_periodic, weighting=weighting)96        return x_n97    m1 = m - 198    steps = get_steps(q=x, is_periodic=is_periodic)99    if weighting is not None:100        steps *= weighting101    # Distribute the waypoints equally along the linear sequences of the initial path102    steps_length = np.linalg.norm(steps, axis=-1)103    if np.sum(steps_length) == 0:104        relative_steps_length = np.full(m1, fill_value=1 / m1)105    else:106        relative_steps_length = steps_length / np.sum(steps_length)107    # Adjust the number of waypoints for each step to make the initial guess as equally spaced as possible108    n_sub_exact = relative_steps_length * (n - 1)109    n_sub = np.round(n_sub_exact).astype(int)110    # If the number of points do not match, change the substeps where the rounding was worst111    n_diff = (n-1) - np.sum(n_sub)112    if n_diff != 0:113        n_sub_acc = n_sub_exact - n_sub114        n_sub_acc = 0.5 + np.sign(n_diff) * n_sub_acc115        idx = np.argsort(n_sub_acc)[-np.abs(n_diff):]116        n_sub[idx] += np.sign(n_diff)117    n_sub_cs = np.hstack((0, n_sub.cumsum())) + 1118    # Add the linear interpolation between the waypoints - step by step for each dimension119    x_n = np.empty((n, d))120    x_n[0, :] = x[0, :].copy()121    for i in range(m1):122        x_n[n_sub_cs[i]:n_sub_cs[i + 1], :] = \123            get_substeps(x=x[i:i + 2, :], n=n_sub[i], is_periodic=is_periodic, include_start=False)124    x_n = periodic_dof_wrapper(x=x_n, is_periodic=is_periodic)125    return x_n126def x2bee(x, n_wp=None):127    x_se = x[..., [0, -1], :]128    if n_wp is None:129        n_wp = x.shape[-2]130    bee = get_substeps(x_se, n=n_wp-1, include_start=True)131    return bee132def x2beerel(x, n_wp=None, eps=1e-4):133    bee = x2bee(x, n_wp=n_wp)134    beerel = x - bee135    d = np.linalg.norm(x[..., -1, :] - x[..., 0, :], axis=-1, keepdims=True)[..., np.newaxis] + eps136    beerel = beerel / d137    return beerel138def beerel2x(beerel, se, eps=1e-4):139    n_wp = beerel.shape[-2]140    assert np.all(beerel[..., [0, -1], :] == 0)141    bee = x2bee(x=se, n_wp=n_wp)142    d = np.linalg.norm(se[..., -1, :] - se[..., 0, :], axis=-1, keepdims=True)[..., np.newaxis] + eps143    x = bee + beerel * d144    return x145def get_path_adjusted(x, n=None, is_periodic=None, weighting=None, __m=5):146    n0 = x.shape[-2]147    if n is None:148        n = n0149    else:150        pass151    return get_substeps_adjusted(x=x, n=(n - 1) * (n0*__m) + 1,152                                 is_periodic=is_periodic, weighting=weighting)[..., ::(n0*__m), :]153def order_path(x, start=None, end=None, is_periodic=None, weights=1.):154    """155    Order the points given by 'x' [2d: (n, d)] according to a weighted euclidean distance156    so that always the nearest point comes next.157    Start with the first point in the array and end with the last if 'x_start' or 'x_end' aren't given.158    """159    # Handle different input combinations160    d = None161    if start is None:162        start = x[..., 0, :]163        x = np.delete(x, 0, axis=-2)164    else:165        d = np.size(start)166    if x is None:167        n = 0168    else:169        n, d = x.shape170    if end is None:171        x_o = np.zeros((n + 1, d))172    else:173        x_o = np.zeros((n + 2, d))174        x_o[-1, :] = end.ravel()175    # Order the points, so that always the nearest is visited next, according to the euclidean distance176    x_o[0, :] = start.ravel()177    for i in range(n):178        x_diff = np.linalg.norm(periodic_dof_wrapper(x - start, is_periodic=is_periodic) * weights, axis=-1)179        i_min = np.argmin(x_diff)180        x_o[1 + i, :] = x[i_min, :]181        start = x[i_min, :]182        x = np.delete(x, i_min, axis=-2)183    return x_o184#185# DERIVATIVES186def d_substeps__dx(n, order=0):187    """188    Get the dependence of substeps ' on the outer way points (x).189    The substeps are placed linear between the waypoints.190    To prevent counting points double one step includes only one of the two endpoints191    This gives a symmetric number of steps but ignores either the start or the end in192    the following calculations.193         x--'--'--'--x---'---'---'---x---'---'---'---x--'--'--'--x--'--'--'--x194    0:  {>         }{>            } {>            } {>         }{>         }195    1:     {         <} {            <} {            <}{         <}{         <}196    Ordering of the waypoints into a matrix:197    0:198    s00 s01 s02 s03 -> step 0 (with start)199    s10 s11 s12 s13200    s20 s21 s22 s23201    s30 s31 s32 s33202    s40 s41 s42 s43 -> step 4 (without end)203    1: (shifting by one, and reordering)204    s01 s02 s03 s10 -> step 0 (without start)205    s11 s12 s13 s20206    s21 s22 s23 s30207    s31 s32 s33 s40208    s41 s42 s43 s50 -> step 4 (with end)209    n          # way points210    n-1        # steps211    n_s        # intermediate points per step212    (n-1)*n_s  # substeps (total)213    n_s = 5214    jac0 = ([[1., 0.8, 0.6, 0.4, 0.2],  # following step  (including way point (1.))215             [0., 0.2, 0.4, 0.6, 0.8]]) # previous step  (excluding way point (1.))216    jac1 = ([[0.2, 0.4, 0.6, 0.8, 1.],  # previous step  (including way point (2.))217             [0.8, 0.6, 0.4, 0.2, 0.]])  # following step  (excluding way point (2.))218    """219    if order == 0:220        jac = (np.arange(n) / n)[np.newaxis, :].repeat(2, axis=0)221        jac[0, :] = 1 - jac[0, :]222    else:223        jac = (np.arange(start=n - 1, stop=-1, step=-1) / n)[np.newaxis, :].repeat(2, axis=0)224        jac[0, :] = 1 - jac[0, :]225    return jac226def combine_d_substeps__dx(d_dxs, n):227    # Combine the jacobians of the sub-way-points (joints) to the jacobian for the optimization variables228    if n <= 1:229        return d_dxs230    if d_dxs.ndim == 3:231        n_samples, n_wp_ss, n_dof = d_dxs.shape232        d_dxs = d_dxs.reshape(n_samples, n_wp_ss//n, n, n_dof)233        ss_jac = d_substeps__dx(n=n, order=1)[np.newaxis, np.newaxis, ..., np.newaxis]234        d_dx = np.einsum('ijkl, ijkl -> ijl', d_dxs, ss_jac[:, :, 0, :, :])235        d_dx[:, :-1, :] += np.einsum('ijkl, ijkl -> ijl', d_dxs[:, 1:, :, :], ss_jac[:, :, 1, :, :])236        return d_dx237    else:238        raise ValueError(f"{d_dxs.ndim}")239def to_spline(x, n_c=4, start_end0=False):240    n_wp, n_dof = x.shape[-2:]241    xx = np.linspace(0, 1, n_wp)242    if np.ndim(x) == 2:243        c = np.zeros((n_c, n_dof))244        for i_d in range(n_dof):245            spl = UnivariateSpline(x=xx, y=x[:, i_d])246            c[..., i_d] = spl.get_coeffs()247    elif np.ndim(x) == 3:248        n = x.shape[0]249        c = np.zeros((n, n_c, n_dof))250        for i_n in range(n):251            for i_d in range(n_dof):252                spl = UnivariateSpline(x=xx, y=x[i_n, :, i_d])253                c[i_n, :, i_d] = spl.get_coeffs()254    else:255        raise ValueError256    if start_end0:257        c = c[..., 1:-1, :]258    return c259def set_spline_coeffs(spl, coeffs):260    data = spl._data  # noqa261    k, n = data[5], data[7]262    data[9][:n - k - 1] = np.ravel(coeffs)263    spl._data = data264def from_spline(c, n_wp, start_end0=False):265    xx = np.linspace(0, 1, n_wp)266    spl = UnivariateSpline(x=xx, y=xx, )267    if start_end0:268        z = np.zeros_like(c[..., :1, :])269        c = np.concatenate((z, c, z), axis=-2)270    n_c, n_dof = c.shape[-2:]271    if np.ndim(c) == 2:272        x = np.zeros((n_wp, n_dof))273        for i_d in range(n_dof):274            set_spline_coeffs(spl, coeffs=c[:, i_d])275            x[:, i_d] = spl(xx)276    elif np.ndim(c) == 3:277        n = c.shape[0]278        x = np.zeros((n, n_wp, n_dof))279        for i_n in range(n):280            for i_d in range(n_dof):281                spl = UnivariateSpline(x=xx, y=x[i_n, :, i_d])282                set_spline_coeffs(spl, coeffs=c[i_n, :, i_d])283                x[i_n, :, i_d] = spl(xx)284    else:285        raise ValueError286    return x287# TODO which way is the best? Start and end MUST match288def fromto_spline(x, n_c=4, start_end0=False):289    return from_spline(c=to_spline(x=x, n_c=n_c, start_end0=start_end0), n_wp=x.shape[-2])290def fromto_spline2(x, n_c=4, start_end0=False):291    n_wp = x.shape[-2]292    x2 = get_steps_between(start=x[..., 0, :], end=x[..., -1, :], n=n_wp)293    dx = x - x2294    c = to_spline(dx, n_c=n_c, start_end0=start_end0)295    dx_spline = from_spline(c=c, n_wp=n_wp)296    x_spline = x2 + dx_spline297    x_spline = get_path_adjusted(x=x_spline)...

test_geometry.py

Source:test_geometry.py

1# -*- coding: utf-8 -*-2import numpy as np3import pytest4import amrex5from amrex import Geometry as Gm6# TODO: return coord?7@pytest.fixture8def box():9    return amrex.Box(amrex.IntVect(0, 0, 0), amrex.IntVect(127, 127, 127))10@pytest.fixture11def real_box():12    return amrex.RealBox([0, 0, 0], [1, 2, 5])13@pytest.fixture14def geometry(box, real_box):15    coord = 116    is_periodic = [0, 0, 1]17    return amrex.Geometry(box, real_box, coord, is_periodic)18def test_geometry_data(box, real_box):19    gd = amrex.GeometryData()20    print(gd.coord)21    assert gd.coord == 022    print(gd.domain)23    print(gd.domain.small_end)24    assert gd.domain.small_end == amrex.IntVect(1, 1, 1)25    print(gd.domain.big_end)26    assert gd.domain.big_end == amrex.IntVect(0, 0, 0)27    print(gd.prob_domain)28    assert amrex.AlmostEqual(gd.prob_domain, amrex.RealBox(0, 0, 0, -1, -1, -1))29    print(gd.isPeriodic())30    print(gd.is_periodic)31    assert gd.is_periodic == gd.isPeriodic() == [0, 0, 0]32    with pytest.raises(AttributeError):33        gd.coord = 134    with pytest.raises(AttributeError):35        gd.domain = box36    with pytest.raises(AttributeError):37        gd.prob_domain = real_box38    with pytest.raises(AttributeError):39        gd.is_periodic = [1, 0, 1]40    with pytest.raises(AttributeError):41        gd.dx = [0.1, 0.2, 0.3]42@pytest.mark.skipif(amrex.Config.spacedim != 3, reason="Requires AMREX_SPACEDIM = 3")43def test_geometry_define(box, real_box):44    gm = Gm()45    coord = 146    is_periodic = [0, 0, 1]47    gm.define(box, real_box, coord, is_periodic)48    assert gm.ProbLength(0) == 1 and gm.ProbLength(1) == 2 and gm.ProbLength(2) == 549    assert gm.isPeriodic() == is_periodic50@pytest.mark.skipif(amrex.Config.spacedim != 3, reason="Requires AMREX_SPACEDIM = 3")51def test_probDomain(box, real_box):52    gm = Gm()53    coord = 154    is_periodic = [0, 0, 1]55    gm.define(box, real_box, coord, is_periodic)56    assert gm.ok()57    lo = [0, -1, 1]58    hi = [1, 0, 2]59    rb = amrex.RealBox(lo, hi)60    gm.ProbDomain(rb)61    assert (62        np.isclose(gm.ProbLo(0), lo[0])63        and np.isclose(gm.ProbLo(1), lo[1])64        and np.isclose(gm.ProbLo(2), lo[2])65        and np.isclose(gm.ProbHi(0), hi[0])66        and np.isclose(gm.ProbHi(1), hi[1])67        and np.isclose(gm.ProbHi(2), hi[2])68    )69@pytest.mark.skipif(amrex.Config.spacedim != 3, reason="Requires AMREX_SPACEDIM = 3")70def test_size(geometry):71    gm = geometry72    assert np.isclose(gm.ProbSize(), 10)73    assert np.isclose(gm.ProbLength(0), 1)74    assert np.isclose(gm.ProbLength(1), 2)75    assert np.isclose(gm.ProbLength(2), 5)76@pytest.mark.skipif(amrex.Config.spacedim != 3, reason="Requires AMREX_SPACEDIM = 3")77def test_domain(box, real_box):78    bx = amrex.Box(amrex.IntVect(0, 0, 0), amrex.IntVect(127, 127, 127))79    gm = Gm()80    coord = 181    is_periodic = [0, 0, 1]82    gm.define(box, real_box, coord, is_periodic)83    assert gm.ok()84    gm.Domain(bx)85    assert gm.Domain().small_end == bx.small_end and gm.Domain().big_end == bx.big_end86@pytest.mark.skipif(amrex.Config.spacedim != 3, reason="Requires AMREX_SPACEDIM = 3")87def test_periodic_queries(box, real_box):88    coord = 189    is_periodic = [0, 0, 1]90    gm = Gm(box, real_box, coord, is_periodic)91    pdcity = gm.periodicity()92    assert gm.isAnyPeriodic()93    assert not gm.isPeriodic(0) and not gm.isPeriodic(1) and gm.isPeriodic(2)94    assert not gm.isAllPeriodic()95    assert gm.isPeriodic() == is_periodic96    gm.setPeriodicity([0, 0, 0])97    assert not gm.isAnyPeriodic()98    gm.setPeriodicity([1, 1, 1])99    assert gm.isAllPeriodic()100@pytest.mark.skipif(amrex.Config.spacedim != 3, reason="Requires AMREX_SPACEDIM = 3")101def test_periodicity(geometry):102    gm = geometry103    bx = gm.Domain()104    for non_periodic_coord in [0, 1]:105        error_thrown = False106        try:107            gm.period(0)108        except RuntimeError:109            error_thrown = True110        assert error_thrown111    assert gm.period(2) == bx.length(2)112    pdcity = amrex.Periodicity(bx.length() * amrex.IntVect(gm.isPeriodic()))113    assert gm.periodicity() == pdcity114    iv1 = amrex.IntVect(0, 0, 0)115    iv2 = amrex.IntVect(9, 19, 29)116    pdcity = amrex.Periodicity(amrex.IntVect(0, 0, 30))117    bx = amrex.Box(iv1, iv2)118    assert gm.periodicity(bx) == pdcity119@pytest.mark.skipif(amrex.Config.spacedim != 3, reason="Requires AMREX_SPACEDIM = 3")120def test_grow(geometry):121    gm = geometry122    gm_grow_pd = gm.growPeriodicDomain(2)123    assert gm_grow_pd.small_end == amrex.IntVect(0, 0, -2)124    assert gm_grow_pd.big_end == amrex.IntVect(127, 127, 129)125    gm_grow_npd = gm.growNonPeriodicDomain(3)126    assert gm_grow_npd.small_end == amrex.IntVect(-3, -3, 0)127    assert gm_grow_npd.big_end == amrex.IntVect(130, 130, 127)128def test_data(geometry, box, real_box):129    geometry_data = geometry.data()130    gd = geometry_data131    assert gd.domain.small_end == box.small_end == gd.Domain().small_end132    assert gd.domain.big_end == box.big_end == gd.Domain().big_end133    assert amrex.AlmostEqual(gd.prob_domain, real_box)134    assert np.allclose(real_box.lo(), gd.prob_domain.lo())135    assert np.allclose(real_box.hi(), gd.prob_domain.hi())136    assert (137        np.isclose(real_box.lo(0), gd.prob_domain.lo(0))138        and np.isclose(real_box.lo(1), gd.prob_domain.lo(1))139        and np.isclose(real_box.lo(2), gd.prob_domain.lo(2))140    )141    assert (142        np.isclose(real_box.hi(0), gd.prob_domain.hi(0))143        and np.isclose(real_box.hi(1), gd.prob_domain.hi(1))144        and np.isclose(real_box.hi(2), gd.prob_domain.hi(2))145    )146    assert np.allclose(real_box.lo(), gd.ProbLo())147    assert np.allclose(real_box.hi(), gd.ProbHi())148    assert (149        np.isclose(real_box.lo(0), gd.ProbLo(0))150        and np.isclose(real_box.lo(1), gd.ProbLo(1))151        and np.isclose(real_box.lo(2), gd.ProbLo(2))152    )153    assert (154        np.isclose(real_box.hi(0), gd.ProbHi(0))155        and np.isclose(real_box.hi(1), gd.ProbHi(1))156        and np.isclose(real_box.hi(2), gd.ProbHi(2))157    )158    assert gd.coord == gd.Coord() == 1159    assert gd.is_periodic == [0, 0, 1]160    assert gd.is_periodic[0] == gd.isPeriodic(0) == 0161    assert gd.is_periodic[1] == gd.isPeriodic(1) == 0162    assert gd.is_periodic[2] == gd.isPeriodic(2) == 1163    print(gd.CellSize())164    assert np.allclose(gd.CellSize(), [0.0078125, 0.015625, 0.0390625])165    assert np.isclose(gd.CellSize(0), 0.0078125)166    assert np.isclose(gd.CellSize(1), 0.015625)167    assert np.isclose(gd.CellSize(2), 0.0390625)168@pytest.mark.skipif(amrex.Config.spacedim != 3, reason="Requires AMREX_SPACEDIM = 3")169def test_coarsen_refine(geometry):170    iv1 = amrex.IntVect(-1, -2, -3)171    iv2 = amrex.IntVect(4, 5, 6)172    bx = amrex.Box(iv1, iv2)173    rb = amrex.RealBox(-1, -2, -3, 2, 4, 6)174    gmc = amrex.Geometry(bx, rb, 1, [0, 0, 1])175    cv = amrex.IntVect(2, 2, 1)176    gmc.coarsen(cv)177    assert gmc.Domain().small_end == amrex.IntVect(-1, -1, -3)178    assert gmc.Domain().big_end == amrex.IntVect(2, 2, 6)179    gmr = amrex.Geometry(bx, rb, 1, [0, 0, 1])180    rv = amrex.IntVect(2, 2, 3)181    gmr.refine(rv)182    assert gmr.Domain().small_end == amrex.IntVect(-2, -4, -9)183    assert gmr.Domain().big_end == amrex.IntVect(9, 11, 20)184@pytest.mark.skipif(amrex.Config.spacedim != 3, reason="Requires AMREX_SPACEDIM = 3")185def test_roundoff_domain():186    iv1 = amrex.IntVect(-1, -2, -3)187    iv2 = amrex.IntVect(4, 5, 6)188    bx = amrex.Box(iv1, iv2)189    rb = amrex.RealBox(0, 1.0002, 0.00105, 2, 4.2, 5)190    gm = Gm(bx, rb, 1, [0, 0, 1])191    assert gm.outsideRoundOffDomain(-1.0, 1, 2)192    assert not gm.outsideRoundOffDomain(1.00, 2.0, 2)193    assert not gm.insideRoundOffDomain(-1.0, 1, 2)194    assert gm.insideRoundOffDomain(1.00, 2.0, 2)195@pytest.mark.skipif(amrex.Config.spacedim != 3, reason="Requires AMREX_SPACEDIM = 3")196def test_Resets():197    rb = amrex.RealBox(0, 0, 0, 1, 2, 6)198    amrex.Geometry.ResetDefaultProbDomain(rb)199    Gm.ResetDefaultProbDomain(rb)200    is_periodic = [1, 0, 1]201    Gm.ResetDefaultPeriodicity(is_periodic)202    Gm.ResetDefaultCoord(1)203    gm = Gm()204    assert (205        np.isclose(gm.ProbLength(0), 1)206        and np.isclose(gm.ProbLength(1), 2)207        and np.isclose(gm.ProbLength(2), 6)208    )209    assert gm.isPeriodic() == is_periodic210    print(gm.Coord())211    CType = amrex.CoordSys.CoordType...

verify.py

Source:verify.py

1from printer import print_line2def set_verification(app_data, is_periodic):3    print_line()4    print("[verify]: Setting the verification values ...")5    verify_data = {}6    verify_data['verified'] = False7    verify_data['epsilon'] = 1.0e-88    verify_value = 0.09    Class = app_data['prob_class']10    if Class == 'S':11        if is_periodic == True:12            verify_value = 0.530770700573e-0413        else:14            verify_value = 0.115028215110e-0115    elif Class == 'W':16        if is_periodic == True:17            verify_value = 0.646732937534e-0518        else:19            verify_value = 0.731581264884e-0120    elif Class == 'A':21        if is_periodic == True:22            verify_value = 0.243336530907e-0523        else:24            verify_value = 0.979991065870e-0125    elif Class == 'B':26        if is_periodic == True:27            verify_value = 0.180056440136e-0528        else:29            verify_value = 0.184378110108e+1930    elif Class == 'C':31        if is_periodic == True:32            verify_value = 0.570673228574e-0633        else:34            verify_value = 0.474623829181e+2435    elif Class == 'D':36        if is_periodic == True:37            verify_value = 0.158327506043e-0938        else:39            verify_value = 0.183242406095e+8440    #fi41    verify_data['verify_value'] = verify_value42    app_data['verify_data'] = verify_data43    return44def verify_norm(app_data):45    print_line()46    print("[verify]: Verifying the results ...")47    verify_data = app_data['verify_data']48    rnm2 = app_data['rnm2']49    verify_value = verify_data['verify_value']50    epsilon = verify_data['epsilon']51    err = abs(rnm2 - verify_value) / verify_value52    if err <= epsilon:53        print("[verify]: VERIFICATION SUCCESSFUL")54        print("[verify]: L2 norm            =", rnm2)55        print("[verify]: Error              =", err)56    else:57        print("[verify]: VERIFICATION FAILED")58        print("[verify]: L2 norm            =", rnm2)59        print("[verify]: Correct L2 norm    =", verify_value)60    #fi61    verify_data['verified'] = True...

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