def test_Wrotate_crossing_fibers():
# Test 2 - simulate crossing fibers intersecting at 70 degrees.
# In this case, diffusion tensor principal eigenvector will be aligned in
# the middle of the crossing fibers. Thus, after rotating the kurtosis
# tensor, this will be equal to a kurtosis tensor simulate of crossing
# fibers both deviating 35 degrees from the x-axis. Moreover, we know that
# crossing fibers will be aligned to the x-y plane, because the smaller
# diffusion eigenvalue, perpendicular to both crossings fibers, will be
# aligned to the z-axis.
# Simulate the crossing fiber
angles = [(90, 30), (90, 30), (20, 30), (20, 30)]
fie = 0.49
frac = [fie*50, (1-fie) * 50, fie*50, (1-fie) * 50]
mevals = np.array([[0.00099, 0, 0], [0.00226, 0.00087, 0.00087],
[0.00099, 0, 0], [0.00226, 0.00087, 0.00087]])
signal, dt, kt = multi_tensor_dki(gtab_2s, mevals, angles=angles,
fractions=frac, snr=None)
evals, evecs = decompose_tensor(from_lower_triangular(dt))
kt_rotated = dki.Wrotate(kt, evecs)
# Now coordinate system has diffusion tensor diagonal aligned to the x-axis
# Simulate the reference kurtosis tensor
angles = [(90, 35), (90, 35), (90, -35), (90, -35)]
signal, dt, kt_ref = multi_tensor_dki(gtab_2s, mevals, angles=angles,
fractions=frac, snr=None)
# Compare rotated with the reference
assert_array_almost_equal(kt_rotated, kt_ref)
def test_Wrotate_single_fiber():
# Rotate the kurtosis tensor of single fiber simulate to the diffusion
# tensor diagonal and check that is equal to the kurtosis tensor of the
# same single fiber simulated directly to the x-axis
# Define single fiber simulate
mevals = np.array([[0.00099, 0, 0], [0.00226, 0.00087, 0.00087]])
fie = 0.49
frac = [fie*100, (1 - fie)*100]
# simulate single fiber not aligned to the x-axis
theta = random.uniform(0, 180)
phi = random.uniform(0, 320)
angles = [(theta, phi), (theta, phi)]
signal, dt, kt = multi_tensor_dki(gtab_2s, mevals, angles=angles,
fractions=frac, snr=None)
evals, evecs = decompose_tensor(from_lower_triangular(dt))
kt_rotated = dki.Wrotate(kt, evecs)
# Now coordinate system has the DT diagonal aligned to the x-axis
# Reference simulation in which DT diagonal is directly aligned to the
# x-axis
angles = (90, 0), (90, 0)
signal, dt_ref, kt_ref = multi_tensor_dki(gtab_2s, mevals, angles=angles,
fractions=frac, snr=None)
assert_array_almost_equal(kt_rotated, kt_ref)
