def test_SphericalTensor(self):
torch.set_default_dtype(torch.float64)
lmax = 6
mul = 1
sphten.SphericalTensor(torch.randn(mul * (lmax + 1) ** 2), mul, lmax)
mul = 3
sphten.SphericalTensor(torch.randn(mul * (lmax + 1) ** 2), mul, lmax)
def test_add(self):
lmax = 4
mul = 1
signal1 = torch.zeros((lmax + 1) ** 2)
signal2 = signal1.clone()
signal1[0] = 1.
signal2[3] = 1.
sph1 = sphten.SphericalTensor(signal1, mul, lmax)
sph2 = sphten.SphericalTensor(signal2, mul, lmax)
new_sph = sph1 + sph2
assert new_sph.mul == mul
assert new_sph.lmax == max(sph1.lmax, sph2.lmax)
def test_mul_and_dot(self):
lmax = 4
mul = 1
signal1 = torch.zeros((lmax + 1) ** 2)
signal2 = signal1.clone()
signal1[0] = 1.
signal2[3] = 1.
sph1 = sphten.SphericalTensor(signal1, mul, lmax)
sph2 = sphten.SphericalTensor(signal2, mul, lmax)
new_sph = sph1 * sph2
assert rs.are_equal(new_sph.Rs, [(rs.mul_dim(sph1.Rs), 0, 0)])
sph1.dot(sph2)
def test_sh_dirac(self):
with o3.torch_default_dtype(torch.float64):
for l in range(5):
angles = torch.tensor(1.2), torch.tensor(2.1)
a = sphten.spherical_harmonics_dirac(torch.stack(o3.angles_to_xyz(*angles), dim=-1), l)
v = sphten.SphericalTensor(a, 1, l).value(*angles)
self.assertAlmostEqual(v.item(), 1)
def test_change_lmax(self):
lmax = 0
mul = 1
signal = torch.zeros(rs.dim([(mul, lmax)]))
sph = sphten.SphericalTensor(signal, mul, lmax)
lmax_new = 5
sph_new = sph.change_lmax(lmax_new)
assert sph_new.signal.shape[0] == rs.dim(sph_new.Rs)