added track average of voronoi area

README.md

@@ -50,7 +50,7 @@ If **Track Analyzer** is run in command line (see below), the data directory mus
 To install **Track Analyzer**, just run:
 
 ```sh
-	pip install track-analyzer`
+	pip install track-analyzer
 ```
 
 ### with a virtualenv

track_analyzer/calculate.py

@@ -550,7 +550,7 @@ def compute_Voronoi(df, frame, groups=None, compute_local_area=True, lengthscale
 
     return {'vor': vor, 'areas': areas}
 
-def compute_all_Voronoi(data_dir, df, outdir=None, compute_local_area=True, area_threshold=3):
+def compute_all_Voronoi(data_dir, df, outdir=None, compute_local_area=True, area_threshold=3, df_mean=None):
     """
     Compute Voronoi tesselation for all frames. Optional: compute Voronoi cell area
     :param data_dir: path to data directory
@@ -563,6 +563,8 @@ def compute_all_Voronoi(data_dir, df, outdir=None, compute_local_area=True, area
     :type compute_local_area: bool
     :param area_threshold: exclusion threshold, above a multiple of area median
     :type area_threshold: float or int
+    :param df_mean: DataFrame containing mean values for each track
+    :type df_mean: pandas.DataFrame
     :return: dict containing voronoi tesselation for each frame as keys
     :rtype: dict
     """
@@ -585,6 +587,15 @@ def compute_all_Voronoi(data_dir, df, outdir=None, compute_local_area=True, area
     pickle_fn = osp.join(outdir, 'voronoi.p')
     pickle.dump(data_dict, open(pickle_fn, "wb"))
 
+    # calculate track average
+    if df_mean is not None:
+        df_mean['area'] = np.nan
+        groups = df.groupby('track')
+        for track in df['track'].unique():
+            traj = groups.get_group(track)
+            ind = df_mean['track'] == track
+            df_mean.loc[ind, 'area'] = traj['area'].mean()
+
     return data_dict
 
 

track_analyzer/plotting.py

@@ -984,11 +984,13 @@ def plot_all_vector_fields(data_dir, df, data, field, plot_on_field=None, dim=3,
                           map_param=map_param, plot_dir=plot_dir, plot_config=plot_config)
 
 
-def plot_all_Voronoi(data_dir, df, data, show_local_area=True,
+def plot_all_Voronoi(data_dir, df, data, show_local_area=True, df_mean = None,
                      image={'image_fn': None, 't_dim': None, 'z_dim': None},
                      map_param={'no_bkg': False, 'vlim': None, 'show_axis': False, 'cmap': 'plasma', 'size_factor': 1},
                      plot_dir=None, plot_config=None, dont_print_count=False):
-    """"""
+    """
+    Plot Voronoi for all frames and calculate voronoi cell area.
+    """
     if plot_dir is None:
         plot_dir = osp.join(data_dir, 'voronoi')
     tpr.safe_mkdir(plot_dir)
@@ -999,9 +1001,9 @@ def plot_all_Voronoi(data_dir, df, data, show_local_area=True,
 
     # get vlim
     if show_local_area:
-        if 'local_area' in df.columns:
+        if 'area' in df.columns:
             if map_param['vlim'] is None:
-                vlim = [df['local_area'].min(), df['local_area'].max()]
+                vlim = [df['area'].min(), df['area'].max()]
                 if vlim == [np.nan, np.nan]:
                     show_local_area = False
                 else:

track_analyzer/scripts/analyze_tracks.py

@@ -153,7 +153,9 @@ def traj_analysis(data_dir, data=None, image=None, refresh=False, parallelize=Fa
         # Voronoi analysis
         if voronoi_config['run']:
             vor_data = tca.compute_all_Voronoi(data_dir, df, outdir=sub_dir,compute_local_area=voronoi_config['compute_local_area'],
-                                            area_threshold=voronoi_config['area_threshold'])
+                                            area_threshold=voronoi_config['area_threshold'],df_mean=df_prop)
+            df_prop.to_csv(mean_fn)
+            
             if voronoi_config['plot']:
                 plot_dir = osp.join(sub_dir, 'voronoi')
                 tpr.safe_mkdir(plot_dir)