def generate_synthetic_model(n_frames, n_basis, n_points):
Bs = np.random.randn(n_basis, 3, n_points) * 10
R = rotvecs_to_Rs(np.random.randn(n_frames, 3))
C = np.random.randn(n_frames, n_basis)
return BasisShapeModel(R, Bs, C=C)
def generate_synthetic_model(n_frames, n_basis, n_points):
Bs = np.random.randn(n_basis, 3, n_points) * 10
R = rotvecs_to_Rs(np.random.randn(n_frames, 3))
C = np.random.randn(n_frames, n_basis)
return BasisShapeModel(R, Bs, C=C)
def test_rot_code():
# It would be very unlikely for any of
F = 10
np.random.seed(0)
# Create a bunch of random rotation vectors.
omega = np.random.randn(F, 3) * 5
# Make sure one has zero norm.
omega[3, :] = 0.0
# Use the sfm implemenation which relies on Rodriguez' formula.
Rs_hat = util.rotvecs_to_Rs(omega)
# Calculate it the slow way using the matrix exponential.
omega_hats = util.hat_operator(omega)
Rs_gt = np.asarray([expm(omega_hat) for omega_hat in omega_hats])
npt.assert_allclose(Rs_hat, Rs_gt)