np.array([[0, 1.5, 0], [
1,
1.5,
0,
], [6, 1.5, 0]]),
np.array([[0, 1.8, 0], [
1,
1.8,
0,
], [6, 1.8, 0]]),
np.array([[0, 0, 0], [2, 2, 0], [4, 4, 0]])
]
tracks = [t.astype(np.float32) for t in tracks]
C = pf.larch_3split(tracks, None, 0.5)
r = fos.ren()
fos.add(r, fos.line(tracks, fos.red))
#fos.show(r)
for c in C:
color = np.random.rand(3)
for i in C[c]['indices']:
fos.add(r, fos.line(tracks[i] + np.array([8., 0., 0.]), color))
fos.add(r, fos.line(tracks[i] + np.array([16., 0., 0.]), color))
fos.add(
r,
fos.line(C[c]['rep3'] / C[c]['N'] + np.array([16., 0., 0.]),
fos.white))
pass'pf.most_similar_track_zhang()
T=pkl.load_pickle(fname)
print 'Reducing the number of points...'
T=[pf.approximate_ei_trajectory(t) for t in T]
print 'Reducing further to tracks with 3 pts...'
T2=[tm.downsample(t,3) for t in T]
print 'LARCH ...'
print 'Splitting ...'
t=time.clock()
C=pf.larch_3split(T2,None,5.)
print time.clock()-t, len(C)
for c in C: print c, C[c]['rep3']/C[c]['N']
r=show_rep3(C)
print 'Merging ...'
t=time.clock()
C=merge(C,5.)
print time.clock()-t, len(C)
for c in C: print c, C[c]['rep3']/C[c]['N']
show_rep3(C,r,fos.red)
for c in C:
pass # pf.most_similar_track_mam()
T = pkl.load_pickle(fname)
print 'Reducing the number of points...'
T = [pf.approx_polygon_track(t) for t in T]
print 'Reducing further to tracks with 3 pts...'
T2 = [tm.downsample(t, 3) for t in T]
print 'LARCH ...'
print 'Splitting ...'
t = time.clock()
C = pf.larch_3split(T2, None, 5.)
print time.clock() - t, len(C)
for c in C:
print c, C[c]['rep3'] / C[c]['N']
r = show_rep3(C)
print 'Merging ...'
t = time.clock()
C = merge(C, 5.)
print time.clock() - t, len(C)
for c in C:
print c, C[c]['rep3'] / C[c]['N']
np.array([[3,0,0],[3.5,1,0],[4,2,0]]),
np.array([[3.2,0,0],[3.7,1,0],[4.4,2,0]]),
np.array([[3.4,0,0],[3.9,1,0],[4.6,2,0]]),
np.array([[0,0.2,0],[1,0.2,0],[2,0.2,0]]),
np.array([[2,0.2,0],[1,0.2,0],[0,0.2,0]]),
np.array([[0,0,0],[0,1,0],[0,2,0]]),
np.array([[0.2,0,0],[0.2,1,0],[0.2,2,0]]),
np.array([[-0.2,0,0],[-0.2,1,0],[-0.2,2,0]]),
np.array([[0,1.5,0],[1,1.5,0,],[6,1.5,0]]),
np.array([[0,1.8,0],[1,1.8,0,],[6,1.8,0]]),
np.array([[0,0,0],[2,2,0],[4,4,0]])]
tracks=[t.astype(np.float32) for t in tracks]
C=pf.larch_3split(tracks,None,0.5)
r=fos.ren()
fos.add(r,fos.line(tracks,fos.red))
#fos.show(r)
for c in C:
color=np.random.rand(3)
for i in C[c]['indices']:
fos.add(r,fos.line(tracks[i]+np.array([8.,0.,0.]),color))
fos.add(r,fos.line(tracks[i]+np.array([16.,0.,0.]),color))
fos.add(r,fos.line(C[c]['rep3']/C[c]['N']+np.array([16.,0.,0.]),fos.white))
fos.show(r)