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 load_tracks(method="pmt"):
from nibabel import trackvis as tv
dname = "/home/eg309/Data/orbital_phantoms/dwi_dir/subject1/"
if method == "pmt":
fname = "/home/eg309/Data/orbital_phantoms/dwi_dir/workflow/tractography/_subject_id_subject1/cam2trk_pico_twoten/data_fit_pdfs_tracked.trk"
streams, hdr = tv.read(fname, points_space="voxel")
tracks = [s[0] for s in streams]
if method == "dti":
fname = dname + "dti_tracks.dpy"
if method == "dsi":
fname = dname + "dsi_tracks.dpy"
if method == "gqs":
fname = dname + "gqi_tracks.dpy"
if method == "eit":
fname = dname + "eit_tracks.dpy"
if method in ["dti", "dsi", "gqs", "eit"]:
dpr_linear = Dpy(fname, "r")
tracks = dpr_linear.read_tracks()
dpr_linear.close()
if method != "pmt":
tracks = [t - np.array([96 / 2.0, 96 / 2.0, 55 / 2.0]) for t in tracks if track_range(t, 100 / 2.5, 150 / 2.5)]
tracks = [t for t in tracks if track_range(t, 100 / 2.5, 150 / 2.5)]
print "final no of tracks ", len(tracks)
qb = QuickBundles(tracks, 25.0 / 2.5, 18)
# from dipy.viz import fvtk
# r=fvtk.ren()
# fvtk.add(r,fvtk.line(qb.virtuals(),fvtk.red))
# fvtk.show(r)
# show_tracks(tracks)#qb.exemplars()[0])
# qb.remove_small_clusters(40)
del tracks
# load
tl = TrackLabeler(qb, qb.downsampled_tracks(), vol_shape=None, tracks_line_width=3.0, tracks_alpha=1)
# return tracks
w = World()
w.add(tl)
# create window
wi = Window(caption="Fos", bgcolor=(1.0, 1.0, 1.0, 1.0), width=1600, height=900)
wi.attach(w)
# create window manager
wm = WindowManager()
wm.add(wi)
wm.run()
def load_PX_tracks():
roi = "LH_premotor"
dn = "/home/hadron/from_John_mon12thmarch"
dname = "/extra_probtrackX_analyses/_subject_id_subj05_101_32/particle2trackvis_" + roi + "_native/"
fname = dn + dname + "tract_samples.trk"
from nibabel import trackvis as tv
points_space = [None, "voxel", "rasmm"]
streamlines, hdr = tv.read(fname, as_generator=True, points_space="voxel")
tracks = [s[0] for s in streamlines]
del streamlines
# return tracks
qb = QuickBundles(tracks, 25.0 / 2.5, 18)
# tl=Line(qb.exemplars()[0],line_width=1)
del tracks
qb.remove_small_clusters(20)
tl = TrackLabeler(qb, qb.downsampled_tracks(), vol_shape=None, tracks_line_width=3.0, tracks_alpha=1)
# put the seeds together
# seeds=np.vstack((seeds,seeds2))
# shif the seeds
# seeds=np.dot(mat[:3,:3],seeds.T).T + mat[:3,3]
# seeds=seeds-shift
# seeds2=np.dot(mat[:3,:3],seeds2.T).T + mat[:3,3]
# seeds2=seeds2-shift
# msk = Point(seeds,colors=(1,0,0,1.),pointsize=2.)
# msk2 = Point(seeds2,colors=(1,0,.ppppp2,1.),pointsize=2.)
w = World()
w.add(tl)
# w.add(msk)
# w.add(msk2)
# w.add(sl)
# create window
wi = Window(caption="Fos", bgcolor=(0.3, 0.3, 0.6, 1.0), width=1600, height=900)
wi.attach(w)
# create window manager
wm = WindowManager()
wm.add(wi)
wm.run()
qb=QuickBundles(T, 20., 12)
#save_pickle(fpkl,qb)
#qb=load_pickle(fpkl)
Init()
title = '[F]oS Streamline Interaction and Segmentation'
w = Window(caption = title,
width = 1200,
height = 800,
bgcolor = (.5, .5, 0.9), right_panel=True)
scene = Scene(scenename = 'Main Scene', activate_aabb = False)
#create the interaction system for tracks
tl = StreamlineLabeler('Bundle Picker',
qb,qb.downsampled_tracks(),
vol_shape=data.shape[:3],
tracks_alpha=1,
affine=affine)
guil = Guillotine('Volume Slicer', data, affine)
scene.add_actor(guil)
scene.add_actor(tl)
w.add_scene(scene)
w.refocus_camera()
Run()
#center
shift=(np.array(data.shape)-1)/2.
T=[t-shift for t in T]
#load initial QuickBundles with threshold 30mm
#fpkl = 'data/subj_05/101_32/DTI/qb_gqi_1M_linear_30.pkl'
qb=QuickBundles(T,25.,30)
print len(qb.clustering)
#qb=load_pickle(fpkl)
qb.remove_small_clusters(1000)
print len(qb.clustering)
#create the interaction system for tracks
tl = TrackLabeler(qb,qb.downsampled_tracks(),vol_shape=data.shape,tracks_line_width=3.,tracks_alpha=1.)
#add a interactive slicing/masking tool
sl = Slicer(affine,data)
#add one way communication between tl and sl
tl.slicer=sl
#OpenGL coordinate system axes
ax = Axes(100)
x,y,z=data.shape
#add the actors to the world
w=World()
w.add(tl)
#w.add(sl)
#w.add(ax)
#create a window
#wi = Window(caption="Interactive bundle selection using fos and QB",\
# bgcolor=(0.3,0.3,0.6,1),width=1600,height=1000)
def set_state(self):
glEnable(GL_DEPTH_TEST)
glEnable(GL_BLEND)
glBlendFunc(GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA)
glEnable(GL_LINE_SMOOTH)
glHint(GL_LINE_SMOOTH_HINT, GL_NICEST)
glLineWidth(self.line_width)
def unset_state(self):
glDisable(GL_DEPTH_TEST)
glDisable(GL_BLEND)
glDisable(GL_LINE_SMOOTH)
glLineWidth(self.line_width)
def delete(self):
for i in range(len(self.vertex_list)):
self.vertex_list[i].delete()
tl = TrackLabeler(qb,qb.downsampled_tracks())
w=World()
w.add(tl)
wi = Window(caption="Tractography Labeler by Free On Shades (http://fos.me)")
wi.attach(w)
wm = WindowManager()
wm.add(wi)
wm.run()
# load initial QuickBundles with threshold 30mm
# fpkl = dname+'data/subj_05/101_32/DTI/qb_gqi_1M_linear_30.pkl'
# qb=QuickBundles(T, 10., 18)
# save_pickle(fpkl,qb)
# qb=load_pickle(fpkl)
qb = QuickBundles(T, 20.0, 12)
# save_pickle(fpkl,qb)
# qb=load_pickle(fpkl)
Init()
title = "[F]oS Streamline Interaction and Segmentation"
w = Window(caption=title, width=1200, height=800, bgcolor=(0.5, 0.5, 0.9), right_panel=True)
scene = Scene(scenename="Main Scene", activate_aabb=False)
# create the interaction system for tracks
tl = StreamlineLabeler(
"Bundle Picker", qb, qb.downsampled_tracks(), vol_shape=data.shape[:3], tracks_alpha=1, affine=affine
)
guil = Guillotine("Volume Slicer", data, affine)
scene.add_actor(guil)
scene.add_actor(tl)
w.add_scene(scene)
w.refocus_camera()
Run()
T = [track for track in T if is_close(track, lT, 5)]
shift = (np.array(ref_shape) - 1) / 2.0
T = [t - shift for t in T]
print len(T)
# save tracks
dpr_linear = Dpy(ftracks, "w")
dpr_linear.write_tracks(T)
dpr_linear.close()
# cluster tracks
qb = QuickBundles(T, 25.0, 25)
# qb.remove_small_clusters(40)
del T
# load
tl = TrackLabeler(qb, qb.downsampled_tracks(), vol_shape=ref_shape, tracks_line_width=3.0, tracks_alpha=1)
fT1 = "data/subj_" + subject + "/MPRAGE_32/T1_flirt_out.nii.gz"
# fT1_ref = '/usr/share/fsl/data/standard/MNI152_T1_1mm_brain.nii.gz'
img = nib.load(fT1)
# img = nib.load(fT1)
sl = Slicer(img.get_affine(), img.get_data())
tl.slicer = sl
luigi = Line([t - shift for t in lT], line_width=2)
# put the seeds together
seeds = np.vstack((seeds, seeds2))
# shif the seeds
seeds = np.dot(mat[:3, :3], seeds.T).T + mat[:3, 3]
seeds = seeds - shift
# seeds2=np.dot(mat[:3,:3],seeds2.T).T + mat[:3,3]
