def testQballOdfModel():
sphere, vecs_xy, bval, bvec, sig = make_fake_signal()
qball_fitter = QballOdfModel(bval, bvec.T, 6, sphere=sphere)
qball_fitter.angular_spacing_threshould = 0.
norm_sig = sig
S = qball_fitter.fit(norm_sig).odf()
stepper = ClosestPeakSelector(qball_fitter, norm_sig, angle_limit=39)
for ii in xrange(len(vecs_xy)):
if np.dot(vecs_xy[ii], [0, 1., 0]) < .84:
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 step is not None
assert np.dot(vecs_xy[ii], step) > .98
step = stepper.next_step(ii, [1., 0, 0.])
assert_array_almost_equal([1., 0, 0.], step)
def testQballOdfModel():
v, e, vecs_xy, bval, bvec, sig = make_fake_signal()
qball_fitter = QballOdfModel(bval, bvec.T, 6, odf_vertices=v, odf_edges=e)
qball_fitter.angular_distance_threshold = 0.0
norm_sig = sig
C = qball_fitter.fit_data(norm_sig)
S = qball_fitter.evaluate_odf(norm_sig)
stepper = ClosestPeakSelector(qball_fitter, norm_sig, angle_limit=39)
for ii in xrange(len(vecs_xy)):
if np.dot(vecs_xy[ii], [0, 1.0, 0]) < 0.84:
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 step is not None
assert np.dot(vecs_xy[ii], step) > 0.98
step = stepper.next_step(ii, [1.0, 0, 0.0])
assert_array_equal([1.0, 0, 0.0], step)
def testQballOdfModel():
v, e, vecs_xy, bval, bvec, sig = make_fake_signal()
qball_fitter = QballOdfModel(bval, bvec.T, 6, odf_vertices=v, odf_edges=e)
qball_fitter.angular_distance_threshold = 0.
norm_sig = sig
C = qball_fitter.fit_data(norm_sig)
S = qball_fitter.evaluate_odf(norm_sig)
stepper = ClosestPeakSelector(qball_fitter, norm_sig, angle_limit=39)
for ii in xrange(len(vecs_xy)):
if np.dot(vecs_xy[ii], [0, 1., 0]) < .84:
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 step is not None
assert np.dot(vecs_xy[ii], step) > .98
step = stepper.next_step(ii, [1., 0, 0.])
assert_array_equal([1., 0, 0.], step)
def testQballOdfModel():
v, e, vecs_xy, bval, bvec, sig = make_fake_signal()
qball_fitter = QballOdfModel(6, bval, bvec, sampling_points=v,
sampling_edges=e)
norm_sig = sig[..., 1:]
C = qball_fitter.fit_data(norm_sig)
S = qball_fitter.evaluate(norm_sig)
stepper = ClosestPeakSelector(qball_fitter, norm_sig, angle_limit=39)
for ii in xrange(len(vecs_xy)):
if np.dot(vecs_xy[ii], [0, 1., 0]) < .84:
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 step is not None
assert np.dot(vecs_xy[ii], step) > .98
step = stepper.next_step(ii, [1., 0, 0.])
assert_array_equal([1., 0, 0.], step)
def testQballOdfModel():
v, e, vecs_xy, bval, bvec, sig = make_fake_signal()
qball_fitter = QballOdfModel(6,
bval,
bvec,
sampling_points=v,
sampling_edges=e)
norm_sig = sig[..., 1:]
C = qball_fitter.fit_data(norm_sig)
S = qball_fitter.evaluate(norm_sig)
stepper = ClosestPeakSelector(qball_fitter, norm_sig, angle_limit=39)
for ii in xrange(len(vecs_xy)):
if np.dot(vecs_xy[ii], [0, 1., 0]) < .84:
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 step is not None
assert np.dot(vecs_xy[ii], step) > .98
step = stepper.next_step(ii, [1., 0, 0.])
assert_array_equal([1., 0, 0.], step)