def test_ClosestPeakSelector():
v, e, vecs_xy, bval, bvec, sig = make_fake_signal()
opdf_fitter = SlowAdcOpdfModel(6,
bval,
bvec,
sampling_points=v,
sampling_edges=e)
norm_sig = sig[..., 1:]
stepper = ClosestPeakSelector(opdf_fitter, norm_sig, angle_limit=49)
C = opdf_fitter.fit_data(norm_sig)
S = opdf_fitter.evaluate(norm_sig)
for ii in xrange(len(vecs_xy)):
if np.dot(vecs_xy[ii], [0, 1., 0]) < .56:
assert_raises(StopIteration, stepper.next_step, ii, [0, 1., 0])
else:
step = stepper.next_step(ii, [0, 1., 0])
s2 = stepper.next_step(ii, vecs_xy[ii])
assert_array_equal(vecs_xy[ii], step)
step = stepper.next_step(ii, [1., 0, 0.])
assert_array_equal([1., 0, 0.], step)
norm_sig.shape = (2, 2, 4, -1)
stepper = ClosestPeakSelector(opdf_fitter, norm_sig, angle_limit=49)
step = stepper.next_step((0, 0, 0), [1, 0, 0])
assert_array_equal(step, [1, 0, 0])
def test_ClosestPeakSelector():
v, e, vecs_xy, bval, bvec, sig = make_fake_signal()
opdf_fitter = SlowAdcOpdfModel(bval,
bvec.T,
6,
odf_vertices=v,
odf_edges=e)
opdf_fitter.angular_distance_threshold = 0.
norm_sig = sig
stepper = ClosestPeakSelector(opdf_fitter, norm_sig, angle_limit=49)
C = opdf_fitter.fit_data(norm_sig)
S = opdf_fitter.evaluate_odf(norm_sig)
for ii in xrange(len(vecs_xy)):
if np.dot(vecs_xy[ii], [0, 1., 0]) < .56:
assert_raises(StopIteration, stepper.next_step, ii, [0, 1., 0])
else:
step = stepper.next_step(ii, [0, 1., 0])
s2 = stepper.next_step(ii, vecs_xy[ii])
assert_array_equal(vecs_xy[ii], step)
step = stepper.next_step(ii, [1., 0, 0.])
assert_array_equal([1., 0, 0.], step)
norm_sig.shape = (2, 2, 4, -1)
stepper = ClosestPeakSelector(opdf_fitter, norm_sig, angle_limit=49)
step = stepper.next_step((0, 0, 0), [1, 0, 0])
assert_array_equal(step, [1, 0, 0])
def test_ClosestPeakSelector():
v, e, vecs_xy, bval, bvec, sig = make_fake_signal()
opdf_fitter = SlowAdcOpdfModel(6, bval, bvec, sampling_points=v, sampling_edges=e)
norm_sig = sig[..., 1:]
stepper = ClosestPeakSelector(opdf_fitter, norm_sig, angle_limit=49)
C = opdf_fitter.fit_data(norm_sig)
S = opdf_fitter.evaluate(norm_sig)
for ii in xrange(len(vecs_xy)):
if np.dot(vecs_xy[ii], [0, 1., 0]) < .56:
assert_raises(StopIteration, stepper.next_step, ii, [0, 1., 0])
else:
step = stepper.next_step(ii, [0, 1., 0])
s2 = stepper.next_step(ii, vecs_xy[ii])
assert_array_equal(vecs_xy[ii], step)
step = stepper.next_step(ii, [1., 0, 0.])
assert_array_equal([1., 0, 0.], step)
norm_sig.shape = (2, 2, 4, -1)
stepper = ClosestPeakSelector(opdf_fitter, norm_sig, angle_limit=49)
step = stepper.next_step((0, 0, 0), [1, 0, 0])
assert_array_equal(step, [1, 0, 0])
def test_ClosestPeakSelector():
v, e, vecs_xy, bval, bvec, sig = make_fake_signal()
opdf_fitter = SlowAdcOpdfModel(bval, bvec.T, 6, odf_vertices=v, odf_edges=e)
opdf_fitter.angular_distance_threshold = 0.0
norm_sig = sig
stepper = ClosestPeakSelector(opdf_fitter, norm_sig, angle_limit=49)
C = opdf_fitter.fit_data(norm_sig)
S = opdf_fitter.evaluate_odf(norm_sig)
for ii in xrange(len(vecs_xy)):
if np.dot(vecs_xy[ii], [0, 1.0, 0]) < 0.56:
assert_raises(StopIteration, stepper.next_step, ii, [0, 1.0, 0])
else:
step = stepper.next_step(ii, [0, 1.0, 0])
s2 = stepper.next_step(ii, vecs_xy[ii])
assert_array_equal(vecs_xy[ii], step)
step = stepper.next_step(ii, [1.0, 0, 0.0])
assert_array_equal([1.0, 0, 0.0], step)
norm_sig.shape = (2, 2, 4, -1)
stepper = ClosestPeakSelector(opdf_fitter, norm_sig, angle_limit=49)
step = stepper.next_step((0, 0, 0), [1, 0, 0])
assert_array_equal(step, [1, 0, 0])
