Use pytest for testing; generalize existing fdtd tests

This commit is contained in:
Jan Petykiewicz 2019-08-04 02:50:09 -07:00
parent 06a491a960
commit 32055ec8d3
2 changed files with 308 additions and 353 deletions

View File

@ -0,0 +1,308 @@
import numpy
import pytest
import dataclasses
from typing import List, Tuple
from numpy.testing import assert_allclose, assert_array_equal
from fdfd_tools import fdtd
prng = numpy.random.RandomState(12345)
def assert_fields_close(a, b, *args, **kwargs):
numpy.testing.assert_allclose(a, b, verbose=False, err_msg='Fields did not match:\n{}\n{}'.format(numpy.rollaxis(a, -1),
numpy.rollaxis(b, -1)), *args, **kwargs)
def assert_close(a, b, *args, **kwargs):
numpy.testing.assert_allclose(a, b, *args, **kwargs)
def test_initial_fields(sim):
# Make sure initial fields didn't change
e0 = sim.es[0]
h0 = sim.hs[0]
j0 = sim.js[0]
mask = (j0 != 0)
assert_fields_close(e0[mask], j0[mask] / sim.epsilon[mask])
assert not e0[~mask].any()
assert not h0.any()
def test_initial_energy(sim):
"""
Assumes fields start at 0 before J0 is added
"""
j0 = sim.js[0]
e0 = sim.es[0]
h0 = sim.hs[0]
h1 = sim.hs[1]
mask = (j0 != 0)
dV = numpy.prod(numpy.meshgrid(*sim.dxes[0], indexing='ij'), axis=0)
u0 = (j0 * j0.conj() / sim.epsilon * dV).sum(axis=0)
args = {'dxes': sim.dxes,
'epsilon': sim.epsilon}
# Make sure initial energy and E dot J are correct
energy0 = fdtd.energy_estep(h0=h0, e1=e0, h2=h1, **args)
e0_dot_j0 = fdtd.delta_energy_j(j0=j0, e1=e0, dxes=sim.dxes)
assert_fields_close(energy0, u0)
assert_fields_close(e0_dot_j0, u0)
def test_energy_conservation(sim):
"""
Assumes fields start at 0 before J0 is added
"""
e0 = sim.es[0]
j0 = sim.js[0]
u = fdtd.delta_energy_j(j0=j0, e1=e0, dxes=sim.dxes).sum()
args = {'dxes': sim.dxes,
'epsilon': sim.epsilon}
for ii in range(1, 8):
u_hstep = fdtd.energy_hstep(e0=sim.es[ii-1], h1=sim.hs[ii], e2=sim.es[ii], **args)
u_estep = fdtd.energy_estep(h0=sim.hs[ii], e1=sim.es[ii], h2=sim.hs[ii + 1], **args)
delta_j_A = fdtd.delta_energy_j(j0=sim.js[ii], e1=sim.es[ii-1], dxes=sim.dxes)
delta_j_B = fdtd.delta_energy_j(j0=sim.js[ii], e1=sim.es[ii], dxes=sim.dxes)
u += delta_j_A.sum()
assert_close(u_hstep.sum(), u)
u += delta_j_B.sum()
assert_close(u_estep.sum(), u)
def test_poynting_divergence(sim):
args = {'dxes': sim.dxes,
'epsilon': sim.epsilon}
dV = numpy.prod(numpy.meshgrid(*sim.dxes[0], indexing='ij'), axis=0)
u_eprev = None
for ii in range(1, 8):
u_hstep = fdtd.energy_hstep(e0=sim.es[ii-1], h1=sim.hs[ii], e2=sim.es[ii], **args)
u_estep = fdtd.energy_estep(h0=sim.hs[ii], e1=sim.es[ii], h2=sim.hs[ii + 1], **args)
delta_j_B = fdtd.delta_energy_j(j0=sim.js[ii], e1=sim.es[ii], dxes=sim.dxes)
du_half_h2e = u_estep - u_hstep - delta_j_B
div_s_h2e = sim.dt * fdtd.poynting_divergence(e=sim.es[ii], h=sim.hs[ii], dxes=sim.dxes) * dV
assert_fields_close(du_half_h2e, -div_s_h2e, rtol=1e-4)
if u_eprev is None:
u_eprev = u_estep
continue
# previous half-step
delta_j_A = fdtd.delta_energy_j(j0=sim.js[ii], e1=sim.es[ii-1], dxes=sim.dxes)
du_half_e2h = u_hstep - u_eprev - delta_j_A
div_s_e2h = sim.dt * fdtd.poynting_divergence(e=sim.es[ii-1], h=sim.hs[ii], dxes=sim.dxes) * dV
assert_fields_close(du_half_e2h, -div_s_e2h, rtol=1e-4)
u_eprev = u_estep
def test_poynting_planes(sim):
mask = (sim.js[0] != 0)
if mask.sum() > 1:
pytest.skip('test_poynting_planes can only test single point sources')
args = {'dxes': sim.dxes,
'epsilon': sim.epsilon}
dV = numpy.prod(numpy.meshgrid(*sim.dxes[0], indexing='ij'), axis=0)
mx = numpy.roll(mask, (-1, -1), axis=(0, 1))
my = numpy.roll(mask, -1, axis=2)
mz = numpy.roll(mask, (+1, -1), axis=(0, 3))
px = numpy.roll(mask, -1, axis=0)
py = mask.copy()
pz = numpy.roll(mask, +1, axis=0)
u_eprev = None
for ii in range(1, 8):
u_hstep = fdtd.energy_hstep(e0=sim.es[ii-1], h1=sim.hs[ii], e2=sim.es[ii], **args)
u_estep = fdtd.energy_estep(h0=sim.hs[ii], e1=sim.es[ii], h2=sim.hs[ii + 1], **args)
s_h2e = -fdtd.poynting(e=sim.es[ii], h=sim.hs[ii]) * sim.dt
s_h2e[0] *= sim.dxes[0][1][None, :, None] * sim.dxes[0][2][None, None, :]
s_h2e[1] *= sim.dxes[0][0][:, None, None] * sim.dxes[0][2][None, None, :]
s_h2e[2] *= sim.dxes[0][0][:, None, None] * sim.dxes[0][1][None, :, None]
planes = [s_h2e[px].sum(), -s_h2e[mx].sum(),
s_h2e[py].sum(), -s_h2e[my].sum(),
s_h2e[pz].sum(), -s_h2e[mz].sum()]
assert_close(sum(planes), (u_estep - u_hstep).sum())
if u_eprev is None:
u_eprev = u_estep
continue
s_e2h = -fdtd.poynting(e=sim.es[ii - 1], h=sim.hs[ii]) * sim.dt
s_e2h[0] *= sim.dxes[0][1][None, :, None] * sim.dxes[0][2][None, None, :]
s_e2h[1] *= sim.dxes[0][0][:, None, None] * sim.dxes[0][2][None, None, :]
s_e2h[2] *= sim.dxes[0][0][:, None, None] * sim.dxes[0][1][None, :, None]
planes = [s_e2h[px].sum(), -s_e2h[mx].sum(),
s_e2h[py].sum(), -s_e2h[my].sum(),
s_e2h[pz].sum(), -s_e2h[mz].sum()]
assert_close(sum(planes), (u_hstep - u_eprev).sum())
# previous half-step
u_eprev = u_estep
## Now tested elsewhere
#def test_j_dot_e(sim):
# for tt in sim.j_steps:
# e0 = sim.es[tt - 1]
# j1 = sim.js[tt]
# e1 = sim.es[tt]
#
# delta_j_A = fdtd.delta_energy_j(j0=j1, e1=e0, dxes=sim.dxes)
# delta_j_B = fdtd.delta_energy_j(j0=j1, e1=e1, dxes=sim.dxes)
#
# args = {'dxes': sim.dxes,
# 'epsilon': sim.epsilon}
#
# u_eprev = fdtd.energy_estep(h0=sim.hs[tt-1], e1=sim.es[tt-1], h2=sim.hs[tt], **args)
# u_hstep = fdtd.energy_hstep(e0=sim.es[tt-1], h1=sim.hs[tt], e2=sim.es[tt], **args)
# u_estep = fdtd.energy_estep(h0=sim.hs[tt], e1=sim.es[tt], h2=sim.hs[tt + 1], **args)
#
# assert_close(delta_j_A.sum(), (u_hstep - u_eprev).sum(), rtol=1e-4)
# assert_close(delta_j_B.sum(), (u_estep - u_hstep).sum(), rtol=1e-4)
@pytest.fixture(scope='module',
params=[(5, 5, 1),
(5, 1, 5),
(5, 5, 5),
# (7, 7, 7),
])
def shape(request):
yield (3, *request.param)
@pytest.fixture(scope='module', params=[0.3])
def dt(request):
yield request.param
@pytest.fixture(scope='module', params=[1.0, 1.5])
def epsilon_bg(request):
yield request.param
@pytest.fixture(scope='module', params=[1.0, 2.5])
def epsilon_fg(request):
yield request.param
@pytest.fixture(scope='module', params=['center', '000', 'random'])
def epsilon(request, shape, epsilon_bg, epsilon_fg):
is3d = (numpy.array(shape) == 1).sum() == 0
if is3d:
if request.param == '000':
pytest.skip('Skipping 000 epsilon because test is 3D (for speed)')
if epsilon_bg != 1:
pytest.skip('Skipping epsilon_bg != 1 because test is 3D (for speed)')
if epsilon_fg not in (1.0, 2.0):
pytest.skip('Skipping epsilon_fg not in (1, 2) because test is 3D (for speed)')
epsilon = numpy.full(shape, epsilon_bg, dtype=float)
if request.param == 'center':
epsilon[:, shape[1]//2, shape[2]//2, shape[3]//2] = epsilon_fg
elif request.param == '000':
epsilon[:, 0, 0, 0] = epsilon_fg
elif request.param == 'random':
epsilon[:] = prng.uniform(low=min(epsilon_bg, epsilon_fg),
high=max(epsilon_bg, epsilon_fg),
size=shape)
yield epsilon
@pytest.fixture(scope='module', params=[1.0])#, 1.5])
def j_mag(request):
yield request.param
@pytest.fixture(scope='module', params=['center', 'random'])
def j_distribution(request, shape, j_mag):
j = numpy.zeros(shape)
if request.param == 'center':
j[:, shape[1]//2, shape[2]//2, shape[3]//2] = j_mag
elif request.param == '000':
j[:, 0, 0, 0] = j_mag
elif request.param == 'random':
j[:] = prng.uniform(low=-j_mag, high=j_mag, size=shape)
yield j
@pytest.fixture(scope='module', params=[1.0, 1.5])
def dx(request):
yield request.param
@pytest.fixture(scope='module', params=['uniform'])
def dxes(request, shape, dx):
if request.param == 'uniform':
dxes = [[numpy.full(s, dx) for s in shape[1:]] for _ in range(2)]
yield dxes
@pytest.fixture(scope='module',
params=[(0,),
(0, 4, 8),
]
)
def j_steps(request):
yield request.param
@dataclasses.dataclass()
class SimResult:
shape: Tuple[int]
dt: float
dxes: List[List[numpy.ndarray]]
epsilon: numpy.ndarray
j_distribution: numpy.ndarray
j_steps: Tuple[int]
es: List[numpy.ndarray] = dataclasses.field(default_factory=list)
hs: List[numpy.ndarray] = dataclasses.field(default_factory=list)
js: List[numpy.ndarray] = dataclasses.field(default_factory=list)
@pytest.fixture(scope='module')
def sim(request, shape, epsilon, dxes, dt, j_distribution, j_steps):
is3d = (numpy.array(shape) == 1).sum() == 0
if is3d:
if dt != 0.3:
pytest.skip('Skipping dt != 0.3 because test is 3D (for speed)')
sim = SimResult(
shape=shape,
dt=dt,
dxes=dxes,
epsilon=epsilon,
j_distribution=j_distribution,
j_steps=j_steps,
)
e = numpy.zeros_like(epsilon)
h = numpy.zeros_like(epsilon)
assert 0 in j_steps
j_zeros = numpy.zeros_like(j_distribution)
eh2h = fdtd.maxwell_h(dt=dt, dxes=dxes)
eh2e = fdtd.maxwell_e(dt=dt, dxes=dxes)
for tt in range(10):
e = e.copy()
h = h.copy()
eh2h(e, h)
eh2e(e, h, epsilon)
if tt in j_steps:
e += j_distribution / epsilon
sim.js.append(j_distribution)
else:
sim.js.append(j_zeros)
sim.es.append(e)
sim.hs.append(h)
return sim

View File

@ -1,353 +0,0 @@
import unittest
import numpy
from fdfd_tools import fdtd
class BasicTests():
def test_initial_fields(self):
# Make sure initial fields didn't change
e0 = self.es[0]
h0 = self.hs[0]
mask = self.src_mask
self.assertEqual(e0[mask], self.j_mag / self.epsilon[mask])
self.assertFalse(e0[~mask].any())
self.assertFalse(h0.any())
def test_initial_energy(self):
e0 = self.es[0]
h0 = self.hs[0]
h1 = self.hs[1]
mask = self.src_mask[1]
dxes = self.dxes if self.dxes is not None else tuple(tuple(numpy.ones(s) for s in e0.shape[1:]) for _ in range(2))
dV = numpy.prod(numpy.meshgrid(*dxes[0], indexing='ij'), axis=0)
u0 = self.j_mag * self.j_mag / self.epsilon[self.src_mask] * dV[mask]
args = {'dxes': self.dxes,
'epsilon': self.epsilon}
# Make sure initial energy and E dot J are correct
energy0 = fdtd.energy_estep(h0=h0, e1=e0, h2=self.hs[1], **args)
e_dot_j_0 = fdtd.delta_energy_j(j0=(e0 - 0) * self.epsilon, e1=e0, dxes=self.dxes)
self.assertEqual(energy0[mask], u0)
self.assertFalse(energy0[~mask].any(), msg='energy0: {}'.format(energy0))
self.assertEqual(e_dot_j_0[mask], u0)
self.assertFalse(e_dot_j_0[~mask].any(), msg='e_dot_j_0: {}'.format(e_dot_j_0))
def test_energy_conservation(self):
e0 = self.es[0]
u0 = fdtd.delta_energy_j(j0=(e0 - 0) * self.epsilon, e1=e0, dxes=self.dxes).sum()
args = {'dxes': self.dxes,
'epsilon': self.epsilon}
for ii in range(1, 8):
with self.subTest(i=ii):
u_hstep = fdtd.energy_hstep(e0=self.es[ii-1], h1=self.hs[ii], e2=self.es[ii], **args)
u_estep = fdtd.energy_estep(h0=self.hs[ii], e1=self.es[ii], h2=self.hs[ii + 1], **args)
self.assertTrue(numpy.allclose(u_hstep.sum(), u0), msg='u_hstep: {}\n{}'.format(u_hstep.sum(), numpy.rollaxis(u_hstep, -1)))
self.assertTrue(numpy.allclose(u_estep.sum(), u0), msg='u_estep: {}\n{}'.format(u_estep.sum(), numpy.rollaxis(u_estep, -1)))
def test_poynting_divergence(self):
args = {'dxes': self.dxes,
'epsilon': self.epsilon}
dxes = self.dxes if self.dxes is not None else tuple(tuple(numpy.ones(s) for s in self.epsilon.shape[1:]) for _ in range(2))
dV = numpy.prod(numpy.meshgrid(*dxes[0], indexing='ij'), axis=0)
u_eprev = None
for ii in range(1, 8):
with self.subTest(i=ii):
u_hstep = fdtd.energy_hstep(e0=self.es[ii-1], h1=self.hs[ii], e2=self.es[ii], **args)
u_estep = fdtd.energy_estep(h0=self.hs[ii], e1=self.es[ii], h2=self.hs[ii + 1], **args)
du_half_h2e = u_estep - u_hstep
div_s_h2e = self.dt * fdtd.poynting_divergence(e=self.es[ii], h=self.hs[ii], dxes=self.dxes) * dV
self.assertTrue(numpy.allclose(du_half_h2e, -div_s_h2e, rtol=1e-4),
msg='du_half_h2e\n{}\ndiv_s_h2e\n{}'.format(numpy.rollaxis(du_half_h2e, -1),
-numpy.rollaxis(div_s_h2e, -1)))
if u_eprev is None:
u_eprev = u_estep
continue
# previous half-step
du_half_e2h = u_hstep - u_eprev
div_s_e2h = self.dt * fdtd.poynting_divergence(e=self.es[ii-1], h=self.hs[ii], dxes=self.dxes) * dV
self.assertTrue(numpy.allclose(du_half_e2h, -div_s_e2h, rtol=1e-4),
msg='du_half_e2h\n{}\ndiv_s_e2h\n{}'.format(numpy.rollaxis(du_half_e2h, -1),
-numpy.rollaxis(div_s_e2h, -1)))
u_eprev = u_estep
def test_poynting_planes(self):
args = {'dxes': self.dxes,
'epsilon': self.epsilon}
dxes = self.dxes if self.dxes is not None else tuple(tuple(numpy.ones(s) for s in self.epsilon.shape[1:]) for _ in range(2))
dV = numpy.prod(numpy.meshgrid(*dxes[0], indexing='ij'), axis=0)
mx = numpy.roll(self.src_mask, (-1, -1), axis=(0, 1))
my = numpy.roll(self.src_mask, -1, axis=2)
mz = numpy.roll(self.src_mask, (+1, -1), axis=(0, 3))
px = numpy.roll(self.src_mask, -1, axis=0)
py = self.src_mask.copy()
pz = numpy.roll(self.src_mask, +1, axis=0)
u_eprev = None
for ii in range(1, 8):
with self.subTest(i=ii):
u_hstep = fdtd.energy_hstep(e0=self.es[ii-1], h1=self.hs[ii], e2=self.es[ii], **args)
u_estep = fdtd.energy_estep(h0=self.hs[ii], e1=self.es[ii], h2=self.hs[ii + 1], **args)
s_h2e = -fdtd.poynting(e=self.es[ii], h=self.hs[ii]) * self.dt
s_h2e[0] *= dxes[0][1][None, :, None] * dxes[0][2][None, None, :]
s_h2e[1] *= dxes[0][0][:, None, None] * dxes[0][2][None, None, :]
s_h2e[2] *= dxes[0][0][:, None, None] * dxes[0][1][None, :, None]
planes = [s_h2e[px].sum(), -s_h2e[mx].sum(),
s_h2e[py].sum(), -s_h2e[my].sum(),
s_h2e[pz].sum(), -s_h2e[mz].sum()]
self.assertTrue(numpy.allclose(sum(planes), (u_estep - u_hstep)[self.src_mask[1]]),
msg='planes: {} (sum: {})\n du:\n {}'.format(planes, sum(planes), (u_estep - u_hstep)[self.src_mask[1]]))
if u_eprev is None:
u_eprev = u_estep
continue
s_e2h = -fdtd.poynting(e=self.es[ii - 1], h=self.hs[ii]) * self.dt
s_e2h[0] *= dxes[0][1][None, :, None] * dxes[0][2][None, None, :]
s_e2h[1] *= dxes[0][0][:, None, None] * dxes[0][2][None, None, :]
s_e2h[2] *= dxes[0][0][:, None, None] * dxes[0][1][None, :, None]
planes = [s_e2h[px].sum(), -s_e2h[mx].sum(),
s_e2h[py].sum(), -s_e2h[my].sum(),
s_e2h[pz].sum(), -s_e2h[mz].sum()]
self.assertTrue(numpy.allclose(sum(planes), (u_hstep - u_eprev)[self.src_mask[1]]),
msg='planes: {} (sum: {})\n du:\n {}'.format(planes, sum(planes), (u_hstep - u_eprev)[self.src_mask[1]]))
# previous half-step
u_eprev = u_estep
class Basic2DNoDXOnlyVacuum(unittest.TestCase, BasicTests):
def setUp(self):
shape = [3, 5, 5, 1]
self.dt = 0.5
self.epsilon = numpy.ones(shape, dtype=float)
self.j_mag = 32
self.dxes = None
self.src_mask = numpy.zeros_like(self.epsilon, dtype=bool)
self.src_mask[1, 2, 2, 0] = True
e = numpy.zeros_like(self.epsilon)
h = numpy.zeros_like(self.epsilon)
e[self.src_mask] = self.j_mag / self.epsilon[self.src_mask]
self.es = [e]
self.hs = [h]
eh2h = fdtd.maxwell_h(dt=self.dt, dxes=self.dxes)
eh2e = fdtd.maxwell_e(dt=self.dt, dxes=self.dxes)
for _ in range(9):
e = e.copy()
h = h.copy()
eh2h(e, h)
eh2e(e, h, self.epsilon)
self.es.append(e)
self.hs.append(h)
class Basic2DUniformDX3(unittest.TestCase, BasicTests):
def setUp(self):
shape = [3, 5, 5, 1]
self.dt = 0.5
self.j_mag = 32
self.dxes = tuple(tuple(numpy.full(s, 2.0) for s in shape[1:]) for _ in range(2))
self.src_mask = numpy.zeros(shape, dtype=bool)
self.src_mask[1, 2, 2, 0] = True
self.epsilon = numpy.full(shape, 1, dtype=float)
self.epsilon[self.src_mask] = 2
e = numpy.zeros_like(self.epsilon)
h = numpy.zeros_like(self.epsilon)
e[self.src_mask] = self.j_mag / self.epsilon[self.src_mask]
self.es = [e]
self.hs = [h]
eh2h = fdtd.maxwell_h(dt=self.dt, dxes=self.dxes)
eh2e = fdtd.maxwell_e(dt=self.dt, dxes=self.dxes)
for _ in range(9):
e = e.copy()
h = h.copy()
eh2h(e, h)
eh2e(e, h, self.epsilon)
self.es.append(e)
self.hs.append(h)
class Basic3DUniformDXOnlyVacuum(unittest.TestCase, BasicTests):
def setUp(self):
shape = [3, 5, 5, 5]
self.dt = 0.5
self.epsilon = numpy.ones(shape, dtype=float)
self.j_mag = 32
self.dxes = tuple(tuple(numpy.ones(s) for s in shape[1:]) for _ in range(2))
self.src_mask = numpy.zeros_like(self.epsilon, dtype=bool)
self.src_mask[1, 2, 2, 2] = True
e = numpy.zeros_like(self.epsilon)
h = numpy.zeros_like(self.epsilon)
e[self.src_mask] = self.j_mag / self.epsilon[self.src_mask]
self.es = [e]
self.hs = [h]
eh2h = fdtd.maxwell_h(dt=self.dt, dxes=self.dxes)
eh2e = fdtd.maxwell_e(dt=self.dt, dxes=self.dxes)
for _ in range(9):
e = e.copy()
h = h.copy()
eh2h(e, h)
eh2e(e, h, self.epsilon)
self.es.append(e)
self.hs.append(h)
class Basic3DUniformDXUniformN(unittest.TestCase, BasicTests):
def setUp(self):
shape = [3, 5, 5, 5]
self.dt = 0.5
self.epsilon = numpy.full(shape, 2, dtype=float)
self.j_mag = 32
self.dxes = tuple(tuple(numpy.ones(s) for s in shape[1:]) for _ in range(2))
self.src_mask = numpy.zeros_like(self.epsilon, dtype=bool)
self.src_mask[1, 2, 2, 2] = True
e = numpy.zeros_like(self.epsilon)
h = numpy.zeros_like(self.epsilon)
e[self.src_mask] = self.j_mag / self.epsilon[self.src_mask]
self.es = [e]
self.hs = [h]
eh2h = fdtd.maxwell_h(dt=self.dt, dxes=self.dxes)
eh2e = fdtd.maxwell_e(dt=self.dt, dxes=self.dxes)
for _ in range(9):
e = e.copy()
h = h.copy()
eh2h(e, h)
eh2e(e, h, self.epsilon)
self.es.append(e)
self.hs.append(h)
class Basic3DUniformDX(unittest.TestCase, BasicTests):
def setUp(self):
shape = [3, 5, 5, 5]
self.dt = 0.33
self.j_mag = 32
self.dxes = tuple(tuple(numpy.ones(s) for s in shape[1:]) for _ in range(2))
self.src_mask = numpy.zeros(shape, dtype=bool)
self.src_mask[1, 2, 2, 2] = True
self.epsilon = numpy.full(shape, 1, dtype=float)
self.epsilon[self.src_mask] = 2
e = numpy.zeros_like(self.epsilon)
h = numpy.zeros_like(self.epsilon)
e[self.src_mask] = self.j_mag / self.epsilon[self.src_mask]
self.es = [e]
self.hs = [h]
eh2h = fdtd.maxwell_h(dt=self.dt, dxes=self.dxes)
eh2e = fdtd.maxwell_e(dt=self.dt, dxes=self.dxes)
for _ in range(9):
e = e.copy()
h = h.copy()
eh2h(e, h)
eh2e(e, h, self.epsilon)
self.es.append(e)
self.hs.append(h)
class Basic3DUniformDX3(unittest.TestCase, BasicTests):
def setUp(self):
shape = [3, 5, 5, 5]
self.dt = 0.5
self.j_mag = 32
self.dxes = tuple(tuple(numpy.full(s, 3.0) for s in shape[1:]) for _ in range(2))
self.src_mask = numpy.zeros(shape, dtype=bool)
self.src_mask[1, 2, 2, 2] = True
self.epsilon = numpy.full(shape, 1, dtype=float)
self.epsilon[self.src_mask] = 2
e = numpy.zeros_like(self.epsilon)
h = numpy.zeros_like(self.epsilon)
e[self.src_mask] = self.j_mag / self.epsilon[self.src_mask]
self.es = [e]
self.hs = [h]
eh2h = fdtd.maxwell_h(dt=self.dt, dxes=self.dxes)
eh2e = fdtd.maxwell_e(dt=self.dt, dxes=self.dxes)
for _ in range(9):
e = e.copy()
h = h.copy()
eh2h(e, h)
eh2e(e, h, self.epsilon)
self.es.append(e)
self.hs.append(h)
class JdotE_3DUniformDX(unittest.TestCase):
def setUp(self):
shape = [3, 5, 5, 5]
self.dt = 0.5
self.j_mag = 32
self.dxes = tuple(tuple(numpy.full(s, 2.0) for s in shape[1:]) for _ in range(2))
self.src_mask = numpy.zeros(shape, dtype=bool)
self.src_mask[1, 2, 2, 2] = True
self.epsilon = numpy.full(shape, 4, dtype=float)
self.epsilon[self.src_mask] = 2
e = numpy.random.randint(-128, 128 + 1, size=shape).astype(float)
h = numpy.random.randint(-128, 128 + 1, size=shape).astype(float)
self.es = [e]
self.hs = [h]
eh2h = fdtd.maxwell_h(dt=self.dt, dxes=self.dxes)
eh2e = fdtd.maxwell_e(dt=self.dt, dxes=self.dxes)
for ii in range(9):
e = e.copy()
h = h.copy()
eh2h(e, h)
eh2e(e, h, self.epsilon)
self.es.append(e)
self.hs.append(h)
if ii == 1:
e[self.src_mask] += self.j_mag / self.epsilon[self.src_mask]
self.j_dot_e = self.j_mag * e[self.src_mask]
def test_j_dot_e(self):
e0 = self.es[2]
j0 = numpy.zeros_like(e0)
j0[self.src_mask] = self.j_mag
u0 = fdtd.delta_energy_j(j0=j0, e1=e0, dxes=self.dxes)
args = {'dxes': self.dxes,
'epsilon': self.epsilon}
ii=2
u_hstep = fdtd.energy_hstep(e0=self.es[ii-1], h1=self.hs[ii], e2=self.es[ii], **args)
u_estep = fdtd.energy_estep(h0=self.hs[ii], e1=self.es[ii], h2=self.hs[ii + 1], **args)
#print(u0.sum(), (u_estep - u_hstep).sum())
self.assertTrue(numpy.allclose(u0.sum(), (u_estep - u_hstep).sum(), rtol=1e-4))