def test_rotate_tree():
m = gtr.rotate(TREE, TEST_UVEC, TEST_ANGLE)
R = gtr._rodriguesToRotationMatrix(TEST_UVEC, TEST_ANGLE)
# rotation matrix inverse equals its transpose
Rinv = R.transpose()
# check that if the inverse rotation on the rotated result returns
# the initial coordinates
_evaluate(TREE, m, lambda x, y: np.allclose(np.dot(Rinv, y), x) )
# check with origin
new_orig = np.array([-50., 45., 30.])
m = gtr.rotate(TREE, TEST_UVEC, TEST_ANGLE, origin=new_orig)
m = gtr.rotate(m, TEST_UVEC, -TEST_ANGLE, origin=new_orig)
_evaluate(TREE, m, lambda x, y: np.allclose(x, y) )
def test_rotate_bad_type_raises():
gtr.rotate("hello", [1,0,0], math.pi)
def test_rotate_neurite_h5():
nrn_a = load_neuron(H5_NRN_PATH)
nrt_a = nrn_a.neurites[0]
nrt_b = gtr.rotate(nrt_a, [0,0,1], math.pi/2.0)
rot = gtr._rodrigues_to_dcm([0,0,1], math.pi/2.0)
_check_fst_neurite_rotate(nrt_a, nrt_b, rot)
def test_rotate_neuron_swc():
nrn_a = load_neuron(SWC_NRN_PATH)
nrn_b = gtr.rotate(nrn_a, [0,0,1], math.pi/2.0)
rot = gtr._rodrigues_to_dcm([0,0,1], math.pi/2.0)
_check_fst_nrn_rotate(nrn_a, nrn_b, rot)
def test_rotate_bad_type_raises():
with pytest.raises(NotImplementedError):
gtr.rotate("hello", [1, 0, 0], math.pi)
def test_rotate_neuron_h5():
nrn_a = load_neuron(H5_NRN_PATH)
nrn_b = gtr.rotate(nrn_a, [0, 0, 1], math.pi/2.0)
rot = gtr._rodrigues_to_dcm([0, 0, 1], math.pi/2.0)
_check_fst_nrn_rotate(nrn_a, nrn_b, rot)
def test_rotate_bad_type_raises():
gtr.rotate("hello", [1,0,0], math.pi)
def test_rotate_neurite_swc():
nrn_a = load_neuron(SWC_NRN_PATH)
nrt_a = nrn_a.neurites[0]
nrt_b = gtr.rotate(nrt_a, [0,0,1], math.pi/2.0)
rot = gtr._rodrigues_to_dcm([0,0,1], math.pi/2.0)
_check_fst_neurite_rotate(nrt_a, nrt_b, rot)
def test_rotate_dispatch():
nt.assert_true(isinstance(gtr.rotate(NEURON, TEST_UVEC, np.pi), Neuron))
nt.assert_true(isinstance(gtr.rotate(TREE, TEST_UVEC, np.pi), Tree))
