#T=T[:1000]

print 'Representing tracks using only 3 pts...'
tracks=[tm.downsample(t,3) for t in T]

print 'Deleting unnecessary data...'
del streams,hdr

print 'Local Skeleton Clustering...'
now=time.clock()
C=pf.local_skeleton_clustering(tracks,d_thr=20)
print 'Done in', time.clock()-now,'s.'

print 'Reducing the number of points...'
T=[pf.approx_polygon_track(t) for t in T]

print 'Showing initial dataset.'

#r=fos.ren()
#fos.add(r,fos.line(T,fos.white,opacity=0.1))
#fos.show(r)



data=T

colors =[np.tile(np.array([1,1,1,opacity],'f'),(len(t),1)) for t in T]

t=Tracks(data,colors,line_width=1.)  
Exemple #2
0
    frame = make_window_maker(trajs, colors)()
    app.MainLoop()

    del frame   
    del app  
    

if __name__ == "__main__":

    #trajs=[100*np.random.rand(10,3),100*np.random.rand(20,3)]    
    #colors=[np.random.rand(3,),np.random.rand(3,)]

    from dipy.io import trackvis as tv
    from dipy.core import track_performance
    #from enthought.mayavi import mlab
    #from enthought.tvtk.api import tvtk

    import numpy as np
    fname='/home/eg309/Data/PBC/pbc2009icdm/brain1/brain1_scan1_fiber_track_mni.trk'
    lines, hdr = tv.read(fname)

    pts = [p[0] for p in lines]
    pts_reduced = [track_performance.approx_polygon_track(p) for p in pts]
    red = np.array([1,0,0])

    trajs=pts_reduced
    colors=[np.array([1.,0,0]) for i in range(len(trajs))]

    show(trajs)

#T=T[:1000]

print 'Representing tracks using only 3 pts...'
tracks = [tm.downsample(t, 3) for t in T]

print 'Deleting unnecessary data...'
del streams, hdr

print 'Local Skeleton Clustering...'
now = time.clock()
C = pf.local_skeleton_clustering(tracks, d_thr=20)
print 'Done in', time.clock() - now, 's.'

print 'Reducing the number of points...'
T = [pf.approx_polygon_track(t) for t in T]

print 'Showing initial dataset.'

#r=fos.ren()
#fos.add(r,fos.line(T,fos.white,opacity=0.1))
#fos.show(r)

data = T

colors = [np.tile(np.array([1, 1, 1, opacity], 'f'), (len(t), 1)) for t in T]

t = Tracks(data, colors, line_width=1.)

t.position = (-100, 0, 0)
Exemple #4
0
    app = wx.PySimpleApp()
    frame = make_window_maker(trajs, colors)()
    app.MainLoop()

    del frame
    del app


if __name__ == "__main__":

    #trajs=[100*np.random.rand(10,3),100*np.random.rand(20,3)]
    #colors=[np.random.rand(3,),np.random.rand(3,)]

    from dipy.io import trackvis as tv
    from dipy.core import track_performance
    #from enthought.mayavi import mlab
    #from enthought.tvtk.api import tvtk

    import numpy as np
    fname = '/home/eg309/Data/PBC/pbc2009icdm/brain1/brain1_scan1_fiber_track_mni.trk'
    lines, hdr = tv.read(fname)

    pts = [p[0] for p in lines]
    pts_reduced = [track_performance.approx_polygon_track(p) for p in pts]
    red = np.array([1, 0, 0])

    trajs = pts_reduced
    colors = [np.array([1., 0, 0]) for i in range(len(trajs))]

    show(trajs)