def show_signals(data,bvals,gradients,sticks=None):
s=data[1:]
s0=data[0]
ls=np.log(s)-np.log(s0)
ind=np.arange(1,data.shape[-1])
ob=-1/bvals[1:]
#lg=np.log(s[1:])-np.log(s0)
d=ob*(np.log(s)-np.log(s0))
r=fvtk.ren()
all=fvtk.crossing(s,ind,gradients,scale=1)
#fvtk.add(r,fvtk.line(all,fvtk.coral))
#d=d-d.min()
#all3=fvtk.crossing(d,ind,gradients,scale=10**4)
#fvtk.add(r,fvtk.line(all3,fvtk.red))
#d=d-d.min()
all2=fvtk.crossing(d,ind,gradients,scale=10**4)
fvtk.add(r,fvtk.line(all2,fvtk.green))
#"""
#d2=d*10**4
#print d2.min(),d2.mean(),d2.max(),d2.std()
for a in all2:
fvtk.label(r,str(np.round(np.linalg.norm(a[0]),2)),pos=a[0],scale=(.2,.2,.2),color=(1,0,0))
if sticks!=None:
for s in sticks:
ln=np.zeros((2,3))
ln[1]=s
fvtk.add(r,fvtk.line(d.max()*10**4*ln,fvtk.blue))
#data2=data.reshape(1,len(data))
#pdi=ProjectiveDiffusivity(data2,bvals,gradients,dotpow=6,width=6,sincpow=2)
#pd=pdi.spherical_diffusivity(data)
#print pd
#"""
fvtk.show(r)
def show_sph_grid():
r=fvtk.ren()
print verts.shape, faces.shape
sph=np.abs(np.dot(gradients[1],verts.T)**2)
print sph.shape
cols=fvtk.colors(sph,'jet')
#fvtk.add(r,fvtk.point(verts,cols,point_radius=.1,theta=10,phi=10))
for (i,v) in enumerate(gradients):
fvtk.label(r,str(i),pos=v,scale=(.02,.02,.02))
if i in [62,76,58]:
fvtk.label(r,str(i),pos=v,scale=(.05,.05,.05),color=(1,0,0))
fvtk.show(r)
def show_zero_level(r,bundle,dist):
T=[downsample(b,12) for b in bundle]
C=local_skeleton_clustering(T,dist)
vs=[]
colors=np.zeros((len(T),3))
for c in C:
vs.append(C[c]['hidden']/C[c]['N'])
color=np.random.rand(3,)
#fvtk.add(r,fvtk.line(vs,color,linewidth=4.5))
for i in C[c]['indices']:
colors[i]=color
fvtk.label(r,text=str(i),pos=(bundle[i][-1]),scale=(.5,.5,.5),color=(color[0],color[1],color[2]))
fvtk.add(r,fvtk.line(T,colors,linewidth=2.))
def test_fvtk_functions():
# Create a renderer
r = fvtk.ren()
# Create 2 lines with 2 different colors
lines = [np.random.rand(10, 3), np.random.rand(20, 3)]
colors = np.random.rand(2, 3)
c = fvtk.line(lines, colors)
fvtk.add(r, c)
# create streamtubes of the same lines and shift them a bit
c2 = fvtk.streamtube(lines, colors)
c2.SetPosition(2, 0, 0)
fvtk.add(r, c2)
# Create a volume and return a volumetric actor using volumetric rendering
vol = 100 * np.random.rand(100, 100, 100)
vol = vol.astype('uint8')
r = fvtk.ren()
v = fvtk.volume(vol)
fvtk.add(r, v)
# Remove all objects
fvtk.rm_all(r)
# Put some text
l = fvtk.label(r, text='Yes Men')
fvtk.add(r, l)
# Slice the volume
fvtk.add(r, fvtk.slicer(vol, plane_i=[50]))
# Change the position of the active camera
fvtk.camera(r, pos=(0.6, 0, 0), verbose=False)
def test_fvtk_functions():
# Create a renderer
r=fvtk.ren()
# Create 2 lines with 2 different colors
lines=[np.random.rand(10,3),np.random.rand(20,3)]
colors=np.random.rand(2,3)
c=fvtk.line(lines,colors)
fvtk.add(r,c)
# Create a volume and return a volumetric actor using volumetric rendering
vol=100*np.random.rand(100,100,100)
vol=vol.astype('uint8')
r = fvtk.ren()
v = fvtk.volume(vol)
fvtk.add(r,v)
# Remove all objects
fvtk.rm_all(r)
# Put some text
l=fvtk.label(r,text='Yes Men')
fvtk.add(r,l)
# Show everything
#fvtk.show(r)
def test_fvtk_functions():
# This tests will fail if any of the given actors changed inputs or do
# not exist
# Create a renderer
r = fvtk.ren()
# Create 2 lines with 2 different colors
lines = [np.random.rand(10, 3), np.random.rand(20, 3)]
colors = np.random.rand(2, 3)
c = fvtk.line(lines, colors)
fvtk.add(r, c)
# create streamtubes of the same lines and shift them a bit
c2 = fvtk.streamtube(lines, colors)
c2.SetPosition(2, 0, 0)
fvtk.add(r, c2)
# Create a volume and return a volumetric actor using volumetric rendering
vol = 100 * np.random.rand(100, 100, 100)
vol = vol.astype('uint8')
r = fvtk.ren()
v = fvtk.volume(vol)
fvtk.add(r, v)
# Remove all objects
fvtk.rm_all(r)
# Put some text
l = fvtk.label(r, text='Yes Men')
fvtk.add(r, l)
# Slice the volume
slicer = fvtk.slicer(vol)
slicer.display(50, None, None)
fvtk.add(r, slicer)
# Change the position of the active camera
fvtk.camera(r, pos=(0.6, 0, 0), verbose=False)
fvtk.clear(r)
# Peak directions
p = fvtk.peaks(np.random.rand(3, 3, 3, 5, 3))
fvtk.add(r, p)
p2 = fvtk.peaks(np.random.rand(3, 3, 3, 5, 3),
np.random.rand(3, 3, 3, 5),
colors=(0, 1, 0))
fvtk.add(r, p2)
def test_fvtk_functions():
# This tests will fail if any of the given actors changed inputs or do
# not exist
# Create a renderer
r = fvtk.ren()
# Create 2 lines with 2 different colors
lines = [np.random.rand(10, 3), np.random.rand(20, 3)]
colors = np.random.rand(2, 3)
c = fvtk.line(lines, colors)
fvtk.add(r, c)
# create streamtubes of the same lines and shift them a bit
c2 = fvtk.streamtube(lines, colors)
c2.SetPosition(2, 0, 0)
fvtk.add(r, c2)
# Create a volume and return a volumetric actor using volumetric rendering
vol = 100 * np.random.rand(100, 100, 100)
vol = vol.astype('uint8')
r = fvtk.ren()
v = fvtk.volume(vol)
fvtk.add(r, v)
# Remove all objects
fvtk.rm_all(r)
# Put some text
l = fvtk.label(r, text='Yes Men')
fvtk.add(r, l)
# Slice the volume
slicer = fvtk.slicer(vol)
slicer.display(50, None, None)
fvtk.add(r, slicer)
# Change the position of the active camera
fvtk.camera(r, pos=(0.6, 0, 0), verbose=False)
fvtk.clear(r)
# Peak directions
p = fvtk.peaks(np.random.rand(3, 3, 3, 5, 3))
fvtk.add(r, p)
p2 = fvtk.peaks(np.random.rand(3, 3, 3, 5, 3),
np.random.rand(3, 3, 3, 5),
colors=(0, 1, 0))
fvtk.add(r, p2)
def main():
parser = buildArgsParser()
args = parser.parse_args()
bvals, bvecs = read_bvals_bvecs(args.bvals, args.bvecs)
ren = fvtk.ren()
if args.points:
points = fvtk.point(bvecs * bvals[..., None] * 0.01,
fvtk.colors.red,
point_radius=.5)
fvtk.add(ren, points)
if args.antipod:
points = fvtk.point(-bvecs * bvals[..., None] * 0.01,
fvtk.colors.green,
point_radius=.5)
fvtk.add(ren, points)
else:
for i in range(bvecs.shape[0]):
label = fvtk.label(ren,
text=str(i),
pos=bvecs[i] * bvals[i] * 0.01,
color=fvtk.colors.red,
scale=(0.5, 0.5, 0.5))
fvtk.add(ren, label)
if args.antipod:
label = fvtk.label(ren,
text=str(i),
pos=-bvecs[i] * bvals[i] * 0.01,
color=fvtk.colors.green,
scale=(0.5, 0.5, 0.5))
fvtk.add(ren, label)
fvtk.show(ren)
def show_gt_streamlines(streamlines, radii, cmap='orient', r=None):
if cmap is None:
np.random.seed(42)
colors = np.random.rand(len(streamlines), 3)
if cmap == 'orient':
colors = line_colors(streamlines)
if r is None:
ren = fvtk.ren()
else:
ren = r
for i in range(len(streamlines)):
line_actor = fvtk.line(streamlines[i],
colors[i],
linewidth=(radii[i, 1] ** 2) / 2.)
fvtk.add(ren, line_actor)
label_actor = fvtk.label(ren, text=str(np.round(radii[i, 1], 2)),
pos=(streamlines[i][0]),
scale=(.8, .8, .8),
color=(colors[i]))
fvtk.add(ren, label_actor)
label_actor_id = fvtk.label(ren, text='[' + str(i) + ']',
pos=(streamlines[i][-1]),
scale=(.8, .8, .8),
color=(colors[i]))
fvtk.add(ren, label_actor_id)
if r is None:
fvtk.show(ren)
else:
return ren
def test_fvtk_functions():
# Create a renderer
r = fvtk.ren()
# Create 2 lines with 2 different colors
lines = [np.random.rand(10, 3), np.random.rand(20, 3)]
colors = np.random.rand(2, 3)
c = fvtk.line(lines, colors)
fvtk.add(r, c)
# Create a volume and return a volumetric actor using volumetric rendering
vol = 100 * np.random.rand(100, 100, 100)
vol = vol.astype('uint8')
r = fvtk.ren()
v = fvtk.volume(vol)
fvtk.add(r, v)
# Remove all objects
fvtk.rm_all(r)
# Put some text
l = fvtk.label(r, text='Yes Men')
fvtk.add(r, l)
print('tripletons %d' % lens.count(3))
"""
Find and display the skeleton of most representative tracks in each cluster:
"""
skeleton=[]
fvtk.clear(r)
for c in C:
bundle=[T[i] for i in C[c]['indices']]
si,s=td.most_similar_track_mam(bundle,'avg')
skeleton.append(bundle[si])
fvtk.label(r,text=str(len(bundle)),pos=(bundle[si][-1]),scale=(2,2,2))
fvtk.add(r,fvtk.line(skeleton,colors,opacity=1))
#fvtk.show(r)
fvtk.record(r,n_frames=1,out_path='fornix_most',size=(600,600))
"""
.. figure:: fornix_most1000000.png
:align: center
**Showing skeleton with the most representative tracks as the skeletal representation**.
The numbers are depicting the number of tracks in each cluster. This is a very compact way to see the underlying
structures an alternative would be to draw the representative tracks with different widths.
"""
print 'With mam_threshold %f we find %d correspondence pairs' % (mam_threshold, np.size(track2track,0))
#fvtk.clear(r)
"""
Now plot the corresponding tracks in the same colours
"""
for row in track2track:
color=np.random.rand(3)
T=[T1[int(row[0])],T3s[int(row[1])]]
fvtk.add(r,fvtk.line(T,color,linewidth=10))
pos1=T1[int(row[0])][0]
pos3=T3s[int(row[1])][0]
fvtk.add(r,fvtk.label(r,str(int(row[0])),tuple(pos1),(5,5,5)))
fvtk.add(r,fvtk.label(r,str(int(row[0])),tuple(pos3),(5,5,5)))
#fvtk.show(r,png_magnify=1)
print('doubletons %d' % lens.count(2))
print('tripletons %d' % lens.count(3))
"""
Find and display the skeleton of most representative tracks in each cluster:
"""
skeleton = []
fvtk.clear(r)
for c in C:
bundle = [T[i] for i in C[c]['indices']]
si, s = td.most_similar_track_mam(bundle, 'avg')
skeleton.append(bundle[si])
fvtk.label(r, text=str(len(bundle)), pos=(bundle[si][-1]), scale=(2, 2, 2))
fvtk.add(r, fvtk.line(skeleton, colors, opacity=1))
#fvtk.show(r)
fvtk.record(r, n_frames=1, out_path='fornix_most', size=(600, 600))
"""
.. figure:: fornix_most1000000.png
:align: center
**Showing skeleton with the most representative tracks as the skeletal representation**.
The numbers are depicting the number of tracks in each cluster. This is a very compact way to see the underlying
structures an alternative would be to draw the representative tracks with different widths.
"""
"""
#fvtk.clear(r)
"""
Now plot the corresponding tracks in the same colours
.. figure:: find_corr1000000.png
:align: center
**Showing correspondence between these two modest tractographies**.
The labels on the corresponding tracks are the indices of the first tractography on the left.
"""
for row in track2track:
color=np.random.rand(3)
T=[T1[int(row[0])],T3s[int(row[1])]]
fvtk.add(r,fvtk.line(T,color,linewidth=5))
pos1=T1[int(row[0])][0]
pos3=T3s[int(row[1])][0]
fvtk.add(r,fvtk.label(r,str(int(row[0])),tuple(pos1),(5,5,5)))
fvtk.add(r,fvtk.label(r,str(int(row[0])),tuple(pos3),(5,5,5)))
# To see in an interactive window:
#fvtk.show(r,png_magnify=1,size=(600,600))
# To make the illustration
print('Saving illustration as find_corr1000000.png')
fvtk.record(r,n_frames=1,out_path='find_corr',size=(600,600))
