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214 lines
6.7 KiB
Python
214 lines
6.7 KiB
Python
from typing import List, Tuple
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import dataclasses
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import pytest # type: ignore
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import numpy # type: ignore
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#from numpy.testing import assert_allclose, assert_array_equal # type: ignore
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from .. import fdtd
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from .utils import assert_close, assert_fields_close, PRNG
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def test_initial_fields(sim):
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# Make sure initial fields didn't change
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e0 = sim.es[0]
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h0 = sim.hs[0]
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j0 = sim.js[0]
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mask = (j0 != 0)
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assert_fields_close(e0[mask], j0[mask] / sim.epsilon[mask])
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assert not e0[~mask].any()
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assert not h0.any()
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def test_initial_energy(sim):
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"""
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Assumes fields start at 0 before J0 is added
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"""
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j0 = sim.js[0]
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e0 = sim.es[0]
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h0 = sim.hs[0]
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h1 = sim.hs[1]
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dV = numpy.prod(numpy.meshgrid(*sim.dxes[0], indexing='ij'), axis=0)
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u0 = (j0 * j0.conj() / sim.epsilon * dV).sum(axis=0)
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args = {'dxes': sim.dxes,
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'epsilon': sim.epsilon}
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# Make sure initial energy and E dot J are correct
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energy0 = fdtd.energy_estep(h0=h0, e1=e0, h2=h1, **args)
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e0_dot_j0 = fdtd.delta_energy_j(j0=j0, e1=e0, dxes=sim.dxes)
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assert_fields_close(energy0, u0)
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assert_fields_close(e0_dot_j0, u0)
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def test_energy_conservation(sim):
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"""
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Assumes fields start at 0 before J0 is added
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"""
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e0 = sim.es[0]
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j0 = sim.js[0]
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u = fdtd.delta_energy_j(j0=j0, e1=e0, dxes=sim.dxes).sum()
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args = {'dxes': sim.dxes,
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'epsilon': sim.epsilon}
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for ii in range(1, 8):
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u_hstep = fdtd.energy_hstep(e0=sim.es[ii - 1], h1=sim.hs[ii], e2=sim.es[ii], **args)
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u_estep = fdtd.energy_estep(h0=sim.hs[ii], e1=sim.es[ii], h2=sim.hs[ii + 1], **args)
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delta_j_A = fdtd.delta_energy_j(j0=sim.js[ii], e1=sim.es[ii - 1], dxes=sim.dxes)
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delta_j_B = fdtd.delta_energy_j(j0=sim.js[ii], e1=sim.es[ii], dxes=sim.dxes)
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u += delta_j_A.sum()
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assert_close(u_hstep.sum(), u)
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u += delta_j_B.sum()
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assert_close(u_estep.sum(), u)
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def test_poynting_divergence(sim):
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args = {'dxes': sim.dxes,
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'epsilon': sim.epsilon}
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u_eprev = None
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for ii in range(1, 8):
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u_hstep = fdtd.energy_hstep(e0=sim.es[ii - 1], h1=sim.hs[ii], e2=sim.es[ii], **args)
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u_estep = fdtd.energy_estep(h0=sim.hs[ii], e1=sim.es[ii], h2=sim.hs[ii + 1], **args)
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delta_j_B = fdtd.delta_energy_j(j0=sim.js[ii], e1=sim.es[ii], dxes=sim.dxes)
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du_half_h2e = u_estep - u_hstep - delta_j_B
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div_s_h2e = sim.dt * fdtd.poynting_divergence(e=sim.es[ii], h=sim.hs[ii], dxes=sim.dxes)
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assert_fields_close(du_half_h2e, -div_s_h2e)
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if u_eprev is None:
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u_eprev = u_estep
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continue
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# previous half-step
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delta_j_A = fdtd.delta_energy_j(j0=sim.js[ii], e1=sim.es[ii - 1], dxes=sim.dxes)
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du_half_e2h = u_hstep - u_eprev - delta_j_A
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div_s_e2h = sim.dt * fdtd.poynting_divergence(e=sim.es[ii - 1], h=sim.hs[ii], dxes=sim.dxes)
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assert_fields_close(du_half_e2h, -div_s_e2h)
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u_eprev = u_estep
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def test_poynting_planes(sim):
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mask = (sim.js[0] != 0).any(axis=0)
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if mask.sum() > 1:
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pytest.skip('test_poynting_planes can only test single point sources, got {}'.format(mask.sum()))
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args = {'dxes': sim.dxes,
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'epsilon': sim.epsilon}
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mx = numpy.roll(mask, -1, axis=0)
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my = numpy.roll(mask, -1, axis=1)
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mz = numpy.roll(mask, -1, axis=2)
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u_eprev = None
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for ii in range(1, 8):
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u_hstep = fdtd.energy_hstep(e0=sim.es[ii - 1], h1=sim.hs[ii], e2=sim.es[ii], **args)
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u_estep = fdtd.energy_estep(h0=sim.hs[ii], e1=sim.es[ii], h2=sim.hs[ii + 1], **args)
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delta_j_B = fdtd.delta_energy_j(j0=sim.js[ii], e1=sim.es[ii], dxes=sim.dxes)
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du_half_h2e = u_estep - u_hstep - delta_j_B
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s_h2e = -fdtd.poynting(e=sim.es[ii], h=sim.hs[ii], dxes=sim.dxes) * sim.dt
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planes = [s_h2e[0, mask].sum(), -s_h2e[0, mx].sum(),
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s_h2e[1, mask].sum(), -s_h2e[1, my].sum(),
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s_h2e[2, mask].sum(), -s_h2e[2, mz].sum()]
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assert_close(sum(planes), du_half_h2e[mask])
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if u_eprev is None:
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u_eprev = u_estep
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continue
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delta_j_A = fdtd.delta_energy_j(j0=sim.js[ii], e1=sim.es[ii - 1], dxes=sim.dxes)
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du_half_e2h = u_hstep - u_eprev - delta_j_A
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s_e2h = -fdtd.poynting(e=sim.es[ii - 1], h=sim.hs[ii], dxes=sim.dxes) * sim.dt
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planes = [s_e2h[0, mask].sum(), -s_e2h[0, mx].sum(),
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s_e2h[1, mask].sum(), -s_e2h[1, my].sum(),
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s_e2h[2, mask].sum(), -s_e2h[2, mz].sum()]
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assert_close(sum(planes), du_half_e2h[mask])
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# previous half-step
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u_eprev = u_estep
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#####################################
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# Test fixtures
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#####################################
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# Also see conftest.py
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@pytest.fixture(params=[0.3])
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def dt(request):
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yield request.param
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@dataclasses.dataclass()
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class TDResult:
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shape: Tuple[int]
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dt: float
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dxes: List[List[numpy.ndarray]]
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epsilon: numpy.ndarray
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j_distribution: numpy.ndarray
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j_steps: Tuple[int]
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es: List[numpy.ndarray] = dataclasses.field(default_factory=list)
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hs: List[numpy.ndarray] = dataclasses.field(default_factory=list)
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js: List[numpy.ndarray] = dataclasses.field(default_factory=list)
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@pytest.fixture(params=[(0, 4, 8)]) # (0,)
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def j_steps(request):
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yield request.param
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@pytest.fixture(params=['center', 'random'])
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def j_distribution(request, shape, j_mag):
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j = numpy.zeros(shape)
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if request.param == 'center':
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j[:, shape[1] // 2, shape[2] // 2, shape[3] // 2] = j_mag
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elif request.param == '000':
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j[:, 0, 0, 0] = j_mag
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elif request.param == 'random':
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j[:] = PRNG.uniform(low=-j_mag, high=j_mag, size=shape)
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yield j
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@pytest.fixture()
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def sim(request, shape, epsilon, dxes, dt, j_distribution, j_steps):
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is3d = (numpy.array(shape) == 1).sum() == 0
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if is3d:
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if dt != 0.3:
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pytest.skip('Skipping dt != 0.3 because test is 3D (for speed)')
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sim = TDResult(
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shape=shape,
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dt=dt,
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dxes=dxes,
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epsilon=epsilon,
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j_distribution=j_distribution,
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j_steps=j_steps,
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)
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e = numpy.zeros_like(epsilon)
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h = numpy.zeros_like(epsilon)
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assert 0 in j_steps
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j_zeros = numpy.zeros_like(j_distribution)
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eh2h = fdtd.maxwell_h(dt=dt, dxes=dxes)
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eh2e = fdtd.maxwell_e(dt=dt, dxes=dxes)
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for tt in range(10):
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e = e.copy()
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h = h.copy()
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eh2h(e, h)
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eh2e(e, h, epsilon)
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if tt in j_steps:
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e += j_distribution / epsilon
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sim.js.append(j_distribution)
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else:
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sim.js.append(j_zeros)
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sim.es.append(e)
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sim.hs.append(h)
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return sim
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