IJ.log(
'Found %d spots in %d tracks.' % (model.getSpots().getNSpots(True),
model.getTrackModel().nTracks(True)))
# Print results in the console.
headerStr = '%10s %10s %10s %10s %10s %10s' % ('Spot_ID', 'Track_ID',
'Frame', 'X', 'Y', 'Z')
rowStr = '%10d %10d %10d %10.1f %10.1f %10.1f'
for i in range(nChannels):
headerStr += (' %10s' % ('C' + str(i + 1)))
rowStr += (' %10.1f')
IJ.log('\n')
IJ.log(headerStr)
tm = model.getTrackModel()
trackIDs = tm.trackIDs(True)
for trackID in trackIDs:
spots = tm.trackSpots(trackID)
# Let's sort them by frame.
ls = ArrayList(spots)
ls.sort(Spot.frameComparator)
for spot in ls:
values = [ spot.ID(), trackID, spot.getFeature('FRAME'), \
spot.getFeature('POSITION_X'), spot.getFeature('POSITION_Y'), spot.getFeature('POSITION_Z') ]
for i in range(nChannels):
values.append(spot.getFeature('MEAN_INTENSITY%02d' % (i + 1)))
IJ.log(rowStr % tuple(values))
IJ.log('TrackMate completed successfully.' )
IJ.log( 'Found %d spots in %d tracks.' % ( model.getSpots().getNSpots( True ) , model.getTrackModel().nTracks( True ) ) )
# Print results in the console.
headerStr = '%10s %10s %10s %10s %10s %10s' % ( 'Spot_ID', 'Track_ID', 'Frame', 'X', 'Y', 'Z' )
rowStr = '%10d %10d %10d %10.1f %10.1f %10.1f'
for i in range( nChannels ):
headerStr += ( ' %10s' % ( 'C' + str(i+1) ) )
rowStr += ( ' %10.1f' )
IJ.log('\n')
IJ.log( headerStr)
tm = model.getTrackModel()
trackIDs = tm.trackIDs( True )
for trackID in trackIDs:
spots = tm.trackSpots( trackID )
# Let's sort them by frame.
ls = ArrayList( spots );
ls.sort( Spot.frameComparator )
for spot in ls:
values = [ spot.ID(), trackID, spot.getFeature('FRAME'), \
spot.getFeature('POSITION_X'), spot.getFeature('POSITION_Y'), spot.getFeature('POSITION_Z') ]
for i in range( nChannels ):
values.append( spot.getFeature( 'MEAN_INTENSITY%02d' % (i+1) ) )
IJ.log( rowStr % tuple( values ) )
