bugfix in subset handling + bugfix in temporal average calculation

doc/source/user_guide/quickstart.rst

@@ -50,7 +50,7 @@ If **Track Analyzer** is run using command lines (see below), the data directory
 - a text file named info.txt containing the metadata (see example)
 - (optional) a tiff file named stack.tif
 - (optional) configuration files in a config directory
-The default config files can be generated by running :code:`TA_config path_to_directory`. The config files are csv files that can be easily edited. 
+The default config files can be generated by running :code:`TA_config <path_to_directory>`. The config files are csv files that can be easily edited. 
 
 ..
   add a section descibing config and info files

track_analyzer/calculate.py

@@ -262,14 +262,25 @@ def interpolate_field(data_dir, df, groups, grids, frame, field_values=['vx', 'v
         if frame_ in df['frame'].unique():
             group_ = groups.get_group(frame_).reset_index(drop=True)
             no_nan_ = group_[np.isfinite(group_[coord_list])]
-            triang = tri.Triangulation(no_nan_['x'].values, no_nan_['y'].values)
-            for coord in field_values:
-                interpolator = tri.LinearTriInterpolator(triang, no_nan_[coord].values)
-                field_dict[coord].append(interpolator(X, Y))
+
+            if no_nan_.shape[0] > 2:  # cannot triangulate with less then 3 points
+                triang = tri.Triangulation(no_nan_['x'].values, no_nan_['y'].values)
+                for coord in field_values:
+                    interpolator = tri.LinearTriInterpolator(triang, no_nan_[coord].values)
+                    field_dict[coord].append(interpolator(X, Y))
+            else:  # make fully masked array 
+                mask = np.ones(X.shape, dtype=bool)
+                marray = np.ma.ones(X.shape)
+                marray[:] = np.nan
+                marray.mask = mask
+                for coord in field_values:
+                    field_dict[coord].append(marray)
+
     for coord in field_values:
         # average interpolated vfield over the frame list
-        stack = np.ma.stack(field_dict[coord], axis=2)
-        field = np.ma.filled(np.sum(stack, axis=2) / len(frame_l), np.nan)
+        stack = np.ma.stack(field_dict[coord], axis=2)  # stack frames along axis 2
+        denom = len(frame_l) - np.sum(stack.mask, axis=2)  # denominator = number of non-masked data for each frame
+        field = np.ma.filled(np.sum(stack, axis=2) / denom, np.nan)
         data[coord] = field
 
     if export_field:

track_analyzer/scripts/analyze_maps.py

@@ -112,7 +112,10 @@ def map_analysis(data_dir, data=None, image=None, refresh=False, parallelize=Fal
         print("WARNING: subsets won't be plotted in different colors in maps if plotted together")
         df_list = [df]  # a single df is kept
     elif subset_analysis == 'separately':
-        df_list = [df[df['subset'] == sub] for sub in df['subset'].unique()]  # a list of df filtered by subset
+        if "subset" in df.columns:
+            df_list = [df[df['subset'] == sub] for sub in df['subset'].unique()]  # a list of df filtered by subset
+        else: 
+            df_list = [df]
 
     # Make grid
     if image['image_size'] is None:  # get image size using data, making it slighlty larger
@@ -137,7 +140,7 @@ def map_analysis(data_dir, data=None, image=None, refresh=False, parallelize=Fal
     for i, df in enumerate(df_list):
         # name subset directory
         dir_name = ''
-        if subset_analysis == 'separately':
+        if subset_analysis == 'separately' and "subset" in df.columns:
             subset_name = df['subset'].values[0]
             dir_name = '_' + subset_name if subset_name != '' else ''
         dir_name_ = '{}{}'.format(len(tpr.listdir_nohidden(map_dir)) + 1, dir_name)

track_analyzer/scripts/make_default_config.py

@@ -42,7 +42,7 @@ def make_default_config(data_dir):
     data_config = tpr.make_data_config(data_dir=data_dir, export_config=True)
     plot_config = tpl.make_plot_config(data_dir=data_dir, export_config=True)
     traj_config = tpr.make_traj_config(data_dir=data_dir, export_config=True)
-    map_config = tpr.make_map_config(data_dir=data_dir, export_config=True)
+    map_config = tpr.make_map_config(data_dir=data_dir, export_config=True,empty_run=False)
 
     config = {'data_config':data_config, 
             'plot_config':plot_config,