def export_trajectories(self, trajectories, filename, movement_type_index=None):
filename = os.path.join(self.settings.out_folder, '%s.pkl' % filename)
plate="PL0"; well="W0" if movement_type_index == None else "W{}".format(movement_type_index)
dict_={plate:{well:ensTraj()}}
cour = dict_[plate][well]
num=0
longueurFilm=0
for movement_type in trajectories:
print movement_type
for i in range(len(trajectories[movement_type])):
print i,
traj=trajectoire(num, id=0)
frame=0
for x,y in trajectories[movement_type][i]:
traj.ajoutPoint(x,y, frame, 0)
frame+=1
traj.density=[4 for k in range(frame)]
cour.add(traj)
num+=1
longueurFilm=max(longueurFilm, frame)
movie_length={plate:{well:longueurFilm}}
connexions= {plate: {well: {}}}
if not os.path.isdir(self.settings.out_folder):
os.mkdir(self.settings.out_folder)
fp = open(filename, 'w')
pickle.dump(dict(zip(['tracklets dictionary', 'connexions between tracklets', 'movie_length'], [dict_, connexions, movie_length])), fp)
fp.close()
return
def trackletBuilder(new_sol, centresFolder, training=False):
'''
J'ajoute un compteur HoleError dans le cas ou Cplex ne respecte pas les contraintes : des cellules ne sont pas atteintes
et par consequent elles ont l'air de surgir de nulle part sans etre apparues via l'algorithme. Je considere que dix erreurs de ce type sont acceptables
par movie
'''
nb_voisins_max=10
#distance_densi=40
stories = ordonnancement(new_sol); res = {}
global movie_length
connexions = {}
for plate in stories:
res.update({plate : {}})
connexions.update({plate : {}})
movie_length.update({plate : {}})
for well in stories[plate]:
count_HoleError=0
print plate, well
ensembleTraj = fHacktrack2.ensTraj()
res[plate].update({well:ensembleTraj})
connexions[plate].update({well:{}})
num = 0; l=[0]; trajC=None
idd=0; firstIndex=min(stories[plate][well].keys());
movie_length[plate].update({well : max(stories[plate][well].keys())-firstIndex+2})
#+2 because there are no tracking in the last frame but it exists
f=open(os.path.join(centresFolder, 'centers_P{}_w{}.pkl'.format(plate, well)), 'r')
lCentersDict=pickle.load(f); f.close()
for index in stories[plate][well]:
print " -----INDEX ", index,
dC={}
lCenters =lCentersDict[index]
nlCenters =lCentersDict[index+1]
treeC = cKDTree(lCenters, leafsize = 10)
nTree = cKDTree(nlCenters, leafsize = 10)
connexions[plate][well].update({index:dC})
solC = stories[plate][well][index]
if type(solC.truth)==str:
l.append(index+1)
continue
singlets = solC.singlets
nextSinglets = solC.nextSinglets
try:
result =solC.result
except AttributeError:
result = filter(lambda x: x[1]==1, zip(solC.hypotheses, solC.truth))
for hyp in result:
s, t = hyp[0]; source = [] ; target = [];
#print hyp
if type(s) in [np.int32, np.uint16] and s!=-1:
source.append(filter(lambda x: x.label == s, singlets)[0])
elif type(s)==tuple:
for c in s:
source.append(filter(lambda x: x.label == c, singlets)[0])
if type(t) in [np.int32, np.uint16] and t!=-1:
target.append(filter(lambda x: x.label == t, nextSinglets)[0])
elif type(t)==tuple:
for c in t:
target.append(filter(lambda x: x.label == c, nextSinglets)[0])
incoming = len(source) ; outcoming= len(target)
mit = (outcoming>1)
mer = (incoming>1)
# if mit or mer:
# print'#####', hyp
if incoming == 0:
#print "APPEAR"
for c in target:
newTraj= fHacktrack2.trajectoire(num, c.center[0], c.center[1], index+1, c.label, idd)
newTraj.addDensity(c.center, nTree, nb_voisins_max, densities)
#print num, idd
ensembleTraj.add(newTraj)
num+=1; idd+=1
continue
elif outcoming ==0:
# print "DISAPPEAR"
if index in l:
#pdb.set_trace()#en fait ce sont au moins les trajectoires qui commencent en 0 et finissent en 0 ie les apparitions disparitions en 0
for c in source:
newTraj = fHacktrack2.trajectoire(num, c.center[0], c.center[1], index, c.label, idd)
#ici c'est une disparititon de trajectoire qui dure une image donc inutile d'ajouter la densite
ensembleTraj.add(newTraj)
num+=1; idd+=1
continue
elif incoming == 1:
#FROM ONE
c = source[0]
incomingTraj = ensembleTraj.findLabelFrame(c.label, index)
if incomingTraj==[]:
#It can happen only at the first frame : trajectories have not been initiated yet
#otherwise I raise HoleError if it has been observed more than 10 times
if index>firstIndex and training==False:
count_HoleError+=1
if count_HoleError>=10:
raise HoleError(plate, well, index)
if not mit:
t=target[0]
newTraj = fHacktrack2.trajectoire(num, c.center[0], c.center[1], index, c.label, idd)
newTraj.addDensity(c.center, treeC, nb_voisins_max, densities)
newTraj.ajoutPoint(t.center[0], t.center[1], index+1, t.label)
newTraj.addDensity(t.center, nTree, nb_voisins_max, densities)
ensembleTraj.add(newTraj)
#print num, idd
num+=1; idd+=1
continue
elif mit:
newTraj = fHacktrack2.trajectoire(num, c.center[0], c.center[1], index, c.label, idd)
newTraj.addDensity(c.center, treeC, nb_voisins_max, densities)
idSource=(idd,)
ensembleTraj.add(newTraj)
num+=1; numC=num; idd+=1; targetCourantes=[];
for t in target:
newTraj = fHacktrack2.trajectoire(numC, t.center[0], t.center[1], index+1, t.label, idd)
newTraj.addDensity(t.center, nTree, nb_voisins_max,densities)
targetCourantes.append(idd)
#print numC, idd
idd+=1
ensembleTraj.add(newTraj)
dC[idSource]=tuple(targetCourantes)
elif not mit:
first = True
traj=incomingTraj[0]
t = target.pop()
traj.ajoutPoint(t.center[0], t.center[1], index+1, t.label)
traj.addDensity(t.center, nTree, nb_voisins_max, densities)
#print traj.numCellule, traj.id
elif mit:
# print 'mit'
first = True; fusion=False; idCourantes=[]; targetCourantes=[]
for i, traj in enumerate(incomingTraj):
idCourantes.append(traj.id)
if first:
numC = incomingTraj[i].numCellule
first=False
fusion=fusion or traj.fusion
incomingTraj[i].numCellule = numC
for t in target:
newTraj = fHacktrack2.trajectoire(numC, t.center[0], t.center[1], index+1, t.label, idd)
newTraj.addDensity(t.center, nTree, nb_voisins_max, densities)
newTraj.fusion = fusion
ensembleTraj.add(newTraj)
targetCourantes.append(idd)
#print numC, idd
idd+=1
dC[tuple(idCourantes)]=tuple(targetCourantes)
elif mer:
if mit:
raise
# print "FROM MORE THAN ONE"
t = target[0]
trajC = fHacktrack2.trajectoire(num, t.center[0], t.center[1], index+1, t.label, idd)
trajC.addDensity(t.center, nTree, nb_voisins_max, densities)
trajC.fusion=True
idTarget=(idd,)
#print num, idd
idd+=1; num+=1; ensembleTraj.add(trajC)
idSource=[]#; tt=[]
for c in source:
incomingTraj = ensembleTraj.findLabelFrame(c.label, index)
try:
#tt.append(incomingTraj[0])
idSource.append(incomingTraj[0].id)
# print incomingTraj[0].numCellule, incomingTraj[0].id
except IndexError:
#donc il faut creer des nouvelles trajectoires
if index>firstIndex and training==False:
count_HoleError+=1
if count_HoleError>=10:
raise HoleError(plate, well, index)
trajC = fHacktrack2.trajectoire(num, c.center[0], c.center[1], index, c.label, idd)
trajC.addDensity(c.center, treeC, nb_voisins_max, densities)
idSource.append(idd)
idd+=1; num+=1
ensembleTraj.add(trajC)
#pdb.set_trace()#dans quel cas peut-on bien tomber ici ??
#on tombe ici a t=0 mais est-ce qu'on y tombe apres ? oui si on calcule les trajectoires du training
#set pcq il y a des evenements elimines par defaut (mvt a quatre)
dC[tuple(idSource)]=idTarget
# print dC
return res, connexions, movie_length
filename = os.path.join(outputFolder, fi); print filename
f=open(filename, 'r')
dataDict = pickle.load(f)
f.close()
except:
sys.stderr.write('Folder {} does not contain densities trajectories file.'.format(outputFolder))
sys.exit()
else:
if not options.simulated:
d,c, movie_length = dataDict['tracklets dictionary'], dataDict['connexions between tracklets'], dataDict['movie_length']
res = histogramPreparationFromTracklets(d, c, outputFolder, False, verbose, movie_length, name=fi_trajfeatures,
filtering_fusion=settings.filtering_fusion,
time_window=time_window)
else:
d=ensTraj()
for traj in dataDict:
t = trajectoire(1, xi=None, yi=None, frame=None, idC=None, id=1)
t.lstPoints = traj
d.lstTraj.append(t)
res=histogramPreparationFromTracklets({options.plate : {options.well : d}}, None,
outputFolder,training =True, verbose=verbose, movie_length={options.plate : {options.well :99}},
name=fi_trajfeatures) #(d,c, outputFolder, False, verbose, tab=True, length=movie_length)
final = time.clock() - initTime
print "##################TEMPS FINAL {}".format(final)
