Merge pull request #144 from SINTEF/silctrack-check-hdf5-files

Tracking update

pysilcam/__init__.py

@@ -1 +1 @@
-__version__ = '0.2.14'
+__version__ = '0.2.15'

pysilcam/config_example.ini

@@ -31,8 +31,10 @@ min_length = 0
 model_path = 'C:/model/keras_model.h5'
 
 [Tracking]
-min_length = 200
-min_speed = 0.000001  # cm/s
-cross_correlation_threshold = 0.1
-ecd_tolerance = 5 # percent
-track_length_limit = 5
+min_length = 200                 # um, Filter particles with major_axis_length less than this.
+min_speed = 0.000001             # cm/s
+cross_correlation_threshold = 0.1  # Shape filter of matching particles, low matches more particles.
+ecd_tolerance = 5                # percent, Size filter on matching particles, high matches more particles
+track_length_limit = 5           # Number of sequential steps required to accept track.
+search_box_steps = 5             # Number of iterations searching for matching parciles
+search_box_size = 10             # pixels, Size of search box used in each step

pysilcam/tracking/silcamtracker.py

@@ -30,6 +30,8 @@ def __init__(self):
         self.DATAFILE = ''
         self.files = None
         self.track_length_limit = 15
+        self.search_box_size = 10  # pixels
+        self.search_box_steps = 5
 
     def initialise(self):
         print('* INITIALISE')
@@ -104,7 +106,9 @@ def process(self):
                 X, Y, ecd, length, width, im_plot = get_vect(img1, img2,
                                                              PIX_SIZE, MIN_LENGTH, GOOD_FIT,
                                                              thresh=self.THRESHOLD,
-                                                             ecd_tolerance=self.ecd_tolerance)
+                                                             ecd_tolerance=self.ecd_tolerance,
+                                                             search_box_size=self.search_box_size,
+                                                             search_box_steps=self.search_box_steps)
             except ValueError:
                 print('  Error getting vectors')
                 continue
@@ -161,7 +165,8 @@ def imc2iml(imc, thresh=0.98):
     return iml
 
 
-def get_vect(img1, img2, PIX_SIZE, MIN_LENGTH, cross_correlation_threshold, thresh=0.98, ecd_tolerance=0):
+def get_vect(img1, img2, PIX_SIZE, MIN_LENGTH, cross_correlation_threshold,
+             thresh=0.98, ecd_tolerance=0, search_box_size=10, search_box_steps=5):
     # label image 2
     iml2 = imc2iml(img2, thresh)
     imbw_out = np.copy(iml2)
@@ -202,9 +207,9 @@ def get_vect(img1, img2, PIX_SIZE, MIN_LENGTH, cross_correlation_threshold, thre
         roi = iml[bbox[0]:bbox[2], bbox[1]:bbox[3]]  # roi of image 1
         roi = roi > 0
 
-        for search_iteration in range(5):
+        for search_iteration in range(search_box_steps):
 
-            search_box = get_search_box(bbox, img2, search_iteration)
+            search_box = get_search_box(bbox, img2, search_iteration, search_box_size)
 
             # extract the roi in which we expect to find a particle
             search_roi = iml2[search_box[0]:search_box[2], search_box[1]:search_box[3]]
@@ -239,8 +244,8 @@ def get_vect(img1, img2, PIX_SIZE, MIN_LENGTH, cross_correlation_threshold, thre
     return X, Y, ecd, length, width, imbw_out
 
 
-def get_search_box(bbox, img2, search_iteration):
-    bbexp = 10 * (search_iteration + 1)  # expansion by this many pixels in all directions
+def get_search_box(bbox, img2, search_iteration, search_box_size=10):
+    bbexp = search_box_size * (search_iteration + 1)  # expansion by this many pixels in all directions
     # establish a search box within image 2 by expanding the particle
     # bounding box from image 1
     r, c = np.shape(img2)

pysilcam/tracking/track.py

@@ -238,6 +238,12 @@ def track_process(configfile, datapath, offset=0):
     '''
     settings = PySilcamSettings(configfile)
 
+    def get_attribute_with_default(obj, attrib, default):
+        if hasattr(obj, attrib):
+            return getattr(obj, attrib)
+        else:
+            return default
+
     sctr = sctracker.Tracker()
     sctr.av_window = settings.Background.num_images
     sctr.MIN_LENGTH = settings.Tracking.min_length
@@ -246,6 +252,8 @@ def track_process(configfile, datapath, offset=0):
     sctr.THRESHOLD = settings.Process.threshold
     sctr.ecd_tolerance = settings.Tracking.ecd_tolerance
     sctr.PIX_SIZE = settings.PostProcess.pix_size
+    sctr.search_box_size = get_attribute_with_default(settings.Tracking, 'search_box_size', 10)
+    sctr.search_box_steps = get_attribute_with_default(settings.Tracking, 'search_box_steps', 5)
 
     sctr.path = datapath
     dataset_name = os.path.split(datapath)[-1] + '-TRACKS'
@@ -276,8 +284,17 @@ def make_boxplot(tracksfile, plotfilename):
     :param tracksfile:
     :return:
     '''
+
+    def has_tracking_data(f, verbose=True):
+        with pd.HDFStore(f, 'r') as f_handle:
+            data_present = '/Tracking/tracks' in f_handle.keys()
+        if verbose and not data_present:
+            print(f"File {f} has no data.")
+        return data_present
+
     h5filedir = os.path.split(tracksfile)[0]
     h5file_list = glob.glob(os.path.join(h5filedir, '*-TRACKS.h5'))
+    h5file_list = [f for f in h5file_list if has_tracking_data(f)]
     dataset_names = [os.path.split(k)[-1].replace('-TRACKS.h5', '') for k in h5file_list]
 
     tracks = dict()
@@ -310,8 +327,8 @@ def silctrack():
 
     Usage:
         silcam-track process <configfile> <datapath> [--offset=<offset>]
-        silcam-track post-process <tracksfile>
-        silcam-track plotting <tracksfile> <plotfilename> [--gif=<outputdir>] [<rawdatapath>] [--boxplot]
+        silcam-track post-process <tracksfile>  [--config=<configfile>]
+        silcam-track plotting <tracksfile> <plotfilename> [--gif=<outputdir>] [<rawdatapath>] [--boxplot] [--config=<configfile>]
     """
 
     args = docopt(silctrack.__doc__)
@@ -332,7 +349,11 @@ def silctrack():
 
     if args['post-process']:
         print('* Load and process')
-        settings = settings_from_h5(args['<tracksfile>'])
+        if args['--config']:
+            settings = PySilcamSettings(args['--config'])
+        else:
+            print('  Using config from h5 file.')
+            settings = settings_from_h5(args['<tracksfile>'])
 
         data, tracks = load_and_process(args['<tracksfile>'],
                                         settings.PostProcess.pix_size,
@@ -346,6 +367,12 @@ def silctrack():
             unfiltered_tracks.to_hdf(fh, 'Tracking/unfiltered_tracks', mode='r+')
 
     if args['plotting']:
+        if args['--config']:
+            settings = PySilcamSettings(args['--config'])
+        else:
+            print('  Using config from h5 file.')
+            settings = settings_from_h5(args['<tracksfile>'])
+
         settings = settings_from_h5(args['<tracksfile>'])
 
         if args['--gif']:
@@ -365,7 +392,7 @@ def silctrack():
 
             make_output_files_for_giffing(unfiltered_tracks, rawdatapath, outputdir,
                                           settings.PostProcess.pix_size,
-                                          track_length_limit=5)
+                                          track_length_limit=settings.Tracking.track_length_limit)
             print('* output files finished.')
             print('use ''convert -delay 12 -loop 0 *.png output.gif'' to make a gif')