def test_qbundles():
streams, hdr = nib.trackvis.read(get_fnames('fornix'))
T = [s[0] for s in streams]
qb = QuickBundles(T, 10., 12)
qb.virtuals()
qb.exemplars()
assert_equal(4, qb.total_clusters)
def test_qbundles():
streams, hdr = nib.trackvis.read(get_data('fornix'))
T = [s[0] for s in streams]
qb = QuickBundles(T, 10., 12)
qb.virtuals()
qb.exemplars()
assert_equal(4, qb.total_clusters)
def half_split_comparisons():
res = {}
for id in range(len(tractography_sizes)):
res[id] = {}
first, second = split_halves(id)
res[id]["lengths"] = [len(first), len(second)]
print len(first), len(second)
first_qb = QuickBundles(first, qb_threshold, downsampling)
n_clus = first_qb.total_clusters
res[id]["nclusters"] = n_clus
print "QB for first half has", n_clus, "clusters"
second_down = [downsample(s, downsampling) for s in second]
matched_random = get_random_streamlines(first_qb.downsampled_tracks(), n_clus)
neighbours_first = count_close_tracks(first_qb.virtuals(), first_qb.downsampled_tracks(), adjacency_threshold)
neighbours_second = count_close_tracks(first_qb.virtuals(), second_down, adjacency_threshold)
neighbours_random = count_close_tracks(matched_random, second_down, adjacency_threshold)
maxclose = np.int(np.max(np.hstack((neighbours_first, neighbours_second, neighbours_random))))
# The numbers of tracks 0, 1, 2, ... 'close' subset tracks
counts = np.array(
[
(
np.int(n),
len(find(neighbours_first == n)),
len(find(neighbours_second == n)),
len(find(neighbours_random == n)),
)
for n in range(maxclose + 1)
],
dtype="f",
)
totals = np.sum(counts[:, 1:], axis=0)
res[id]["totals"] = totals
res[id]["counts"] = counts
# print totals
# print counts
missed_fractions = counts[0, 1:] / totals
res[id]["missed_fractions"] = missed_fractions
means = np.sum(counts[:, 1:] * counts[:, [0, 0, 0]], axis=0) / totals
# print means
res[id]["means"] = means
# print res
return res
def test_qbundles():
streams, hdr = nib.trackvis.read(get_data('fornix'))
T = [s[0] for s in streams]
Trk = np.array(T, dtype=np.object)
qb = QuickBundles(T, 10., 12)
Tqb = qb.virtuals()
# Tqbe,Tqbei=qb.exemplars(T)
Tqbe, Tqbei = qb.exemplars()
assert_equal(4, qb.total_clusters)
from pyglet.window import key
from fos.core.utils import screen_to_model
import fos.core.collision as cll
from pyglet.gl import *
#dipy modules
from dipy.segment.quickbundles import QuickBundles
streams,hdr = nib.trackvis.read(get_track_filename())
#center the data
T=[s[0] for s in streams]
mean_T=np.mean(np.concatenate(T),axis=0)
T=[t-mean_T for t in T]
qb=QuickBundles(T,10.,12)
Tqb=qb.virtuals()
Tqbe,Tqbei=qb.exemplars()
class TrackLabeler(Actor):
def __init__(self,qb,tracks,colors=None,line_width=2.,affine=None):
self.virtuals=qb.virtuals()
self.tracks=tracks
if affine is None:
self.affine = np.eye(4, dtype = np.float32)
else:
self.affine = affine
#aabb - bounding box things
ccurves=np.concatenate(tracks)
self.min=np.min(ccurves,axis=0)
