def test_matrix_norm(self):
"""Compute matrix norm of forward/backward projector using power
norm. """
geom = Geometry(2)
proj_vec = Rn(geom.proj_size).element(1)
# Compute norm for simple least squares
cp = ODLChambollePock(geom, proj_vec)
self.assertEqual(cp.adj_scal_fac, 1)
mat_norm0 = cp.matrix_norm(iterations=4,
vol_init=1,
intermediate_results=True)
self.assertTrue(mat_norm0[-1] > 0)
# Resume computation
mat_norm1, vol = cp.matrix_norm(iterations=3,
vol_init=1, intermediate_results=True,
return_volume=True)
mat_norm2 = cp.matrix_norm(iterations=4, vol_init=vol,
intermediate_results=True)
self.assertNotEqual(mat_norm0[0], mat_norm2[0])
self.assertEqual(mat_norm0[3], mat_norm2[0])
# Compute norm for TV
mat_norm3 = cp.matrix_norm(iterations=4, vol_init=1, tv_norm=True,
intermediate_results=True)
self.assertFalse(np.array_equal(mat_norm2, mat_norm3))
print('LS unit init volume:', mat_norm2)
print('TV unit init volume:', mat_norm3)
# Use non-homogeneous initial volume
v0 = np.random.rand(geom.vol_size)
mat_norm4 = cp.matrix_norm(iterations=4, vol_init=v0, tv_norm=False,
intermediate_results=True)
mat_norm5 = cp.matrix_norm(iterations=4, vol_init=v0, tv_norm=True,
intermediate_results=True)
print('LS random init volume:', mat_norm4)
print('TV random init volume:', mat_norm5)
# test with adjoint scaling factor for backprojector
self.assertEqual(cp.adj_scal_fac, 1)
cp.adjoint_scaling_factor()
self.assertFalse(cp.adj_scal_fac == 1)
print('adjoint scaling factor:', cp.adj_scal_fac)
mat_norm6 = cp.matrix_norm(iterations=4, vol_init=1, tv_norm=False,
intermediate_results=True)
mat_norm7 = cp.matrix_norm(iterations=4, vol_init=1, tv_norm=True,
intermediate_results=True)
print('LS init volume, adjoint rescaled:', mat_norm6)
print('TV init volume, adjoint rescaled:', mat_norm7)
