def test_cut_plane():
dt = np.dtype(np.float32)
refx = np.array([[0,0,0],[1,0,0],[2,0,0],[3,0,0]],dtype=dt)
bundlex = [np.array([[0.5,1,0],[1.5,2,0],[2.5,3,0]],dtype=dt),
np.array([[0.5,2,0],[1.5,3,0],[2.5,4,0]],dtype=dt),
np.array([[0.5,1,1],[1.5,2,2],[2.5,3,3]],dtype=dt),
np.array([[-0.5,2,-1],[-1.5,3,-2],[-2.5,4,-3]],dtype=dt)]
expected_hit0 = [
[ 1. , 1.5 , 0. , 0.70710683, 0. ],
[ 1. , 2.5 , 0. , 0.70710677, 1. ],
[ 1. , 1.5 , 1.5 , 0.81649661, 2. ]]
expected_hit1 = [
[ 2. , 2.5 , 0. , 0.70710677, 0. ],
[ 2. , 3.5 , 0. , 0.70710677, 1. ],
[ 2. , 2.5 , 2.5 , 0.81649655, 2. ]]
hitx=pf.cut_plane(bundlex,refx)
yield assert_array_almost_equal, hitx[0], expected_hit0
yield assert_array_almost_equal, hitx[1], expected_hit1
# check that algorithm allows types other than float32
bundlex[0] = np.asarray(bundlex[0], dtype=np.float64)
hitx=pf.cut_plane(bundlex,refx)
yield assert_array_almost_equal, hitx[0], expected_hit0
yield assert_array_almost_equal, hitx[1], expected_hit1
refx = np.asarray(refx, dtype=np.float64)
hitx=pf.cut_plane(bundlex,refx)
yield assert_array_almost_equal, hitx[0], expected_hit0
yield assert_array_almost_equal, hitx[1], expected_hit1
def test_cut_plane():
dt = np.dtype(np.float32)
refx = np.array([[0, 0, 0], [1, 0, 0], [2, 0, 0], [3, 0, 0]], dtype=dt)
bundlex = [
np.array([[0.5, 1, 0], [1.5, 2, 0], [2.5, 3, 0]], dtype=dt),
np.array([[0.5, 2, 0], [1.5, 3, 0], [2.5, 4, 0]], dtype=dt),
np.array([[0.5, 1, 1], [1.5, 2, 2], [2.5, 3, 3]], dtype=dt),
np.array([[-0.5, 2, -1], [-1.5, 3, -2], [-2.5, 4, -3]], dtype=dt)
]
expected_hit0 = [[1., 1.5, 0., 0.70710683, 0.],
[1., 2.5, 0., 0.70710677, 1.],
[1., 1.5, 1.5, 0.81649661, 2.]]
expected_hit1 = [[2., 2.5, 0., 0.70710677, 0.],
[2., 3.5, 0., 0.70710677, 1.],
[2., 2.5, 2.5, 0.81649655, 2.]]
hitx = pf.cut_plane(bundlex, refx)
yield assert_array_almost_equal, hitx[0], expected_hit0
yield assert_array_almost_equal, hitx[1], expected_hit1
# check that algorithm allows types other than float32
bundlex[0] = np.asarray(bundlex[0], dtype=np.float64)
hitx = pf.cut_plane(bundlex, refx)
yield assert_array_almost_equal, hitx[0], expected_hit0
yield assert_array_almost_equal, hitx[1], expected_hit1
refx = np.asarray(refx, dtype=np.float64)
hitx = pf.cut_plane(bundlex, refx)
yield assert_array_almost_equal, hitx[0], expected_hit0
yield assert_array_almost_equal, hitx[1], expected_hit1
def refconc(brain, ref, divergence_threshold=0.3, fibre_weight=0.7):
'''
given a reference fibre locates the parallel fibres in brain (tracks)
with threshold_hitdata applied to cut_planes output then follows
with concentration to locate the locus of a neck
'''
hitdata = pf.cut_plane(brain, ref)
reduced_hitdata, heavy_weight_fibres = threshold_hitdata(hitdata, divergence_threshold, fibre_weight)
#index, centre, log_max_concentration = max_concentration(reduced_hitdata, ref)
index=None
centre=None
log_max_concentration=None
return heavy_weight_fibres, index, centre
def refconc(brain, ref, divergence_threshold=0.3, fibre_weight=0.7):
'''
given a reference fibre locates the parallel fibres in brain (tracks)
with threshold_hitdata applied to cut_planes output then follows
with concentration to locate the locus of a neck
'''
hitdata = pf.cut_plane(brain, ref)
reduced_hitdata, heavy_weight_fibres = threshold_hitdata(hitdata, divergence_threshold, fibre_weight)
#index, centre, log_max_concentration = max_concentration(reduced_hitdata, ref)
index=None
centre=None
log_max_concentration=None
return heavy_weight_fibres, index, centre
