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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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