def test_openmp_locks():
static = []
moving = []
pts = 20
for i in range(1000):
s = np.random.rand(pts, 3)
static.append(s)
moving.append(s + 2)
moving = moving[2:]
points, offsets = unlist_streamlines(static)
points2, offsets2 = unlist_streamlines(moving)
D = np.zeros((len(offsets), len(offsets2)), dtype='f8')
_bundle_minimum_distance_matrix(points, points2, len(offsets),
len(offsets2), pts, D)
dist1 = 0.25 * (np.sum(np.min(D, axis=0)) / float(D.shape[1]) +
np.sum(np.min(D, axis=1)) / float(D.shape[0]))**2
dist2 = _bundle_minimum_distance(points, points2, len(offsets),
len(offsets2), pts)
assert_almost_equal(dist1, dist2, 6)
def test_openmp_locks():
static = []
moving = []
pts = 20
for i in range(1000):
s = np.random.rand(pts, 3)
static.append(s)
moving.append(s + 2)
moving = moving[2:]
points, offsets = unlist_streamlines(static)
points2, offsets2 = unlist_streamlines(moving)
D = np.zeros((len(offsets), len(offsets2)), dtype='f8')
_bundle_minimum_distance_matrix(points, points2,
len(offsets), len(offsets2),
pts, D)
dist1 = 0.25 * (np.sum(np.min(D, axis=0)) / float(D.shape[1]) +
np.sum(np.min(D, axis=1)) / float(D.shape[0])) ** 2
dist2 = _bundle_minimum_distance(points, points2,
len(offsets), len(offsets2),
pts)
assert_almost_equal(dist1, dist2, 6)
def test_unlist_relist_streamlines():
streamlines = [np.random.rand(10, 3), np.random.rand(20, 3), np.random.rand(5, 3)]
points, offsets = unlist_streamlines(streamlines)
assert_equal(offsets.dtype, np.dtype("i8"))
assert_equal(points.shape, (35, 3))
assert_equal(len(offsets), len(streamlines))
streamlines2 = relist_streamlines(points, offsets)
assert_equal(len(streamlines), len(streamlines2))
for i in range(len(streamlines)):
assert_array_equal(streamlines[i], streamlines2[i])
def test_unlist_relist_streamlines():
streamlines = [np.random.rand(10, 3),
np.random.rand(20, 3),
np.random.rand(5, 3)]
points, offsets = unlist_streamlines(streamlines)
assert_equal(offsets.dtype, np.dtype('i8'))
assert_equal(points.shape, (35, 3))
assert_equal(len(offsets), len(streamlines))
streamlines2 = relist_streamlines(points, offsets)
assert_equal(len(streamlines), len(streamlines2))
for i in range(len(streamlines)):
assert_array_equal(streamlines[i], streamlines2[i])
def test_efficient_bmd():
a = np.array([[1, 1, 1],
[2, 2, 2],
[3, 3, 3]])
streamlines = [a, a + 2, a + 4]
points, offsets = unlist_streamlines(streamlines)
points = points.astype(np.double)
points2 = points.copy()
D = np.zeros((len(offsets), len(offsets)), dtype='f8')
_bundle_minimum_distance_matrix(points, points2,
len(offsets), len(offsets),
a.shape[0], D)
assert_equal(np.sum(np.diag(D)), 0)
points2 += 2
_bundle_minimum_distance_matrix(points, points2,
len(offsets), len(offsets),
a.shape[0], D)
streamlines2 = relist_streamlines(points2, offsets)
D2 = distance_matrix_mdf(streamlines, streamlines2)
assert_array_almost_equal(D, D2)
cols = D2.shape[1]
rows = D2.shape[0]
dist = 0.25 * (np.sum(np.min(D2, axis=0)) / float(cols) +
np.sum(np.min(D2, axis=1)) / float(rows)) ** 2
dist2 = _bundle_minimum_distance(points, points2,
len(offsets), len(offsets),
a.shape[0])
assert_almost_equal(dist, dist2)
def write_ply(fname,
data,
comments=['DTI Tractography, produced by fiber-track']):
"""
Write bundles to ply file
:param fname:
:param data:
:param comments:
:return:
"""
points, idx = unlist_streamlines(data)
with open(fname, 'w') as f:
f.write('ply\nformat ascii 1.0\n')
for com in comments:
f.write('comment ' + com + '\n')
f.write('element vertices ' + str(len(points)))
f.write('\nproperty float x\nproperty float y\nproperty float z\n')
f.write('element fiber {}\nproperty int endindex'.format(len(idx)))
f.write('\nend_header\n')
for vert in points:
f.write(
str(vert[0]) + ' ' + str(vert[1]) + ' ' + str(vert[2]) + '\n')
for i in idx:
f.write(str(i) + '\n')
def _set_moving(self, moving):
self.moving_centered_pts, _ = unlist_streamlines(moving)
def _set_static(self, static):
static_centered_pts, st_idx = unlist_streamlines(static)
self.static_centered_pts = np.ascontiguousarray(static_centered_pts,
dtype=np.float64)
self.block_size = st_idx[0]
def _set_moving(self, moving):
self.moving_centered_pts, _ = unlist_streamlines(moving)
def _set_static(self, static):
static_centered_pts, st_idx = unlist_streamlines(static)
self.static_centered_pts = np.ascontiguousarray(static_centered_pts,
dtype=np.float64)
self.block_size = st_idx[0]
