def test_translate_inertia(translation):
shape = PlatonicFamily()("Cube")
# Choose a volume > 1 to test the volume scaling, but don't choose one
# that's too large because the uncentered polyhedral calculation has
# massive error without fixing that.
shape.volume = 2
shape.center = (0, 0, 0)
translated_shape = ConvexPolyhedron(shape.vertices + translation)
translated_inertia = translate_inertia_tensor(
translation, shape.inertia_tensor, shape.volume
)
mc_tensor = compute_inertia_mc(translated_shape.vertices, 1e4)
assert np.allclose(
translated_inertia,
translated_shape._compute_inertia_tensor(False),
atol=2e-1,
rtol=2e-1,
)
assert np.allclose(
mc_tensor, translated_shape._compute_inertia_tensor(False), atol=2e-1, rtol=2e-1
)
assert np.allclose(mc_tensor, translated_inertia, atol=1e-2, rtol=1e-2)
assert np.allclose(mc_tensor, translated_shape.inertia_tensor, atol=1e-2, rtol=1e-2)
def testfun(translation):
translated_convex_cube = ConvexPolyhedron(convex_cube.vertices +
translation)
translated_inertia = translate_inertia_tensor(
translation, convex_cube_inertia_tensor, convex_cube_volume)
mc_tensor = compute_inertia_mc(translated_convex_cube.vertices,
convex_cube_volume, 1e4)
uncentered_inertia_tensor = translated_convex_cube._compute_inertia_tensor(
False)
assert np.allclose(
translated_inertia,
uncentered_inertia_tensor,
atol=2e-1,
rtol=2e-1,
)
assert np.allclose(mc_tensor,
uncentered_inertia_tensor,
atol=2e-1,
rtol=2e-1)
assert np.allclose(mc_tensor, translated_inertia, atol=1e-2, rtol=1e-2)
assert np.allclose(mc_tensor,
translated_convex_cube.inertia_tensor,
atol=1e-2,
rtol=1e-2)
def test_moment_inertia_damasceno_shapes(shape):
# These shapes pass the test for a sufficiently high number of samples, but
# the number is too high to be worth running them regularly.
bad_shapes = [
"Augmented Truncated Dodecahedron",
"Deltoidal Hexecontahedron",
"Disdyakis Triacontahedron",
"Truncated Dodecahedron",
"Truncated Icosidodecahedron",
"Metabiaugmented Truncated Dodecahedron",
"Pentagonal Hexecontahedron",
"Paragyrate Diminished Rhombicosidodecahedron",
"Square Cupola",
"Triaugmented Truncated Dodecahedron",
"Parabiaugmented Truncated Dodecahedron",
]
if shape["name"] in ["RESERVED", "Sphere"] + bad_shapes:
return
np.random.seed(0)
poly = ConvexPolyhedron(shape["vertices"])
num_samples = 1000
accept = False
# Loop over different sampling rates to minimize the test runtime.
while num_samples < 1e8:
try:
coxeter_result = poly.inertia_tensor
mc_result = compute_inertia_mc(shape["vertices"], num_samples)
assert np.allclose(coxeter_result, mc_result, atol=1e-1)
accept = True
break
except AssertionError:
num_samples *= 10
continue
if not accept:
raise AssertionError(
"The test failed for shape {}.\nMC Result: "
"\n{}\ncoxeter result: \n{}".format(
shape["name"], mc_result, coxeter_result
)
)