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(T,A,IND,VERTS,scale):
r=fvtk.ren()
fvtk.clear(r)
fvtk.add(r,fvtk.line(T,fvtk.red))
fvtk.show(r)
Td=[downsample(t,20) for t in T]
C=local_skeleton_clustering(Td,3)
fvtk.clear(r)
lent=float(len(T))
for c in C:
color=np.random.rand(3)
virtual=C[c]['hidden']/float(C[c]['N'])
if length(virtual)> virtual_thr:
linewidth=100*len(C[c]['indices'])/lent
if linewidth<1.:
linewidth=1
#fvtk.add(r,fvtk.line(virtual,color,linewidth=linewidth))
#fvtk.add(r,fvtk.label(r,str(len(C[c]['indices'])),pos=virtual[0],scale=3,color=color ))
#print C[c]['hidden'].shape
print A.shape
print IND.shape
print VERTS.shape
all,allo=fvtk.crossing(A,IND,VERTS,scale,True)
colors=np.zeros((len(all),3))
for (i,a) in enumerate(all):
if allo[i][0]==0 and allo[i][1]==0 and allo[i][2]==1:
pass
else:
colors[i]=cm.boys2rgb(allo[i])
fvtk.add(r,fvtk.line(all,colors))
fvtk.show(r)
We locate 3 contiguous voxels [3,8,4], [3,8,5], and [3,8,6] which have respectively 1, 2, and 3 crossings. ``fvtk.crossing`` is a helper function which we use to graph the orientations of the maxima of all the voxels in our dataset. We use 3 different colourings and offset the graphs to display them in one diagram. The colourings are: - all blue, with the 3 voxels used above ([3,8,4], [3,8,5], and [3,8,6]) marked in blue, indigo, and red. - the Boys' colour map (see ``colormap.boys2rgb.py``) - the orientation colour map (see ``colormap.orient2rgb.py`` with red: left-right; green: anteroposterior; blue: superior-inferior. """ #3,8,4 no crossing no_cross = fvtk.crossing(QA[3, 8, 4], IN[3, 8, 4], verts, 1) #3,8,5 crossing cross = fvtk.crossing(QA[3, 8, 5], IN[3, 8, 5], verts, 1) #3,8,6 double crossing dcross = fvtk.crossing(QA[3, 8, 6], IN[3, 8, 6], verts, 1) all, allo = fvtk.crossing(QA, IN, verts, 1, True) fvtk.add(r, fvtk.line(all, fvtk.azure, linewidth=1.)) no_cross_shift = [c + np.array([3, 8, 4]) for c in no_cross] cross_shift = [c + np.array([3, 8, 5]) for c in cross] dcross_shift = [c + np.array([3, 8, 6]) for c in dcross] fvtk.add(r, fvtk.line(no_cross_shift, fvtk.blue, linewidth=5.))
We locate 3 contiguous voxels [3,8,4], [3,8,5], and [3,8,6] which have respectively 1, 2, and 3 crossings. ``fvtk.crossing`` is a helper function which we use to graph the orientations of the maxima of all the voxels in our dataset. We use 3 different colourings and offset the graphs to display them in one diagram. The colourings are: - all blue, with the 3 voxels used above ([3,8,4], [3,8,5], and [3,8,6]) marked in blue, indigo, and red. - the Boys' colour map (see ``colormap.boys2rgb.py``) - the orientation colour map (see ``colormap.orient2rgb.py`` with red: left-right; green: anteroposterior; blue: superior-inferior. """ #3,8,4 no crossing no_cross=fvtk.crossing(QA[3,8,4],IN[3,8,4],verts,1) #3,8,5 crossing cross=fvtk.crossing(QA[3,8,5],IN[3,8,5],verts,1) #3,8,6 double crossing dcross=fvtk.crossing(QA[3,8,6],IN[3,8,6],verts,1) all,allo=fvtk.crossing(QA,IN,verts,1,True) fvtk.add(r,fvtk.line(all,fvtk.azure,linewidth=1.)) no_cross_shift=[c+np.array([3,8,4]) for c in no_cross] cross_shift=[c+np.array([3,8,5]) for c in cross] dcross_shift=[c+np.array([3,8,6]) for c in dcross] fvtk.add(r,fvtk.line(no_cross_shift,fvtk.blue,linewidth=5.))