def _get_large_cell_normals(s1, s2):
dp = get_distinguished_points(s1, s2)
normals = Rodrigues.zero(dp.shape + (2, ))
planes1 = dp.axis * np.tan(dp.angle.data / 4)
planes2 = -dp.axis * np.tan(dp.angle.data / 4)**-1
planes2.data[np.isnan(planes2.data)] = 0
normals[:, 0] = planes1
normals[:, 1] = planes2
normals: Rotation = Rotation.from_neo_euler(normals).flatten().unique(
antipodal=False)
if not normals.size:
return normals
_, inv = normals.axis.unique(return_inverse=True)
axes_unique = []
angles_unique = []
for i in np.unique(inv):
n = normals[inv == i]
axes_unique.append(n.axis.data[0])
angles_unique.append(n.angle.data.max())
normals = Rotation.from_neo_euler(
AxAngle.from_axes_angles(np.array(axes_unique), angles_unique))
return normals
def test_get_distinguished_points(s1, s2, expected):
dp = get_distinguished_points(s1, s2)
assert np.allclose(dp.data, expected, atol=1e-3)
