bugfix: default filters parameters are loaded if missing

track_analyzer/prepare.py

@@ -1337,8 +1337,8 @@ def make_data_config(data_dir=None, export_config=True):
     Initialize parameters used by get_data
     :param data_dir: path to data directory
     :type data_dir: str or None
-    :param export_to_config: to export to config file
-    :type export_to_config: bool
+    :param export_config: to export to config file
+    :type export_config: bool
     :return: filters used by select_sub_data()
     :rtype: dict
     """
@@ -1361,13 +1361,13 @@ def make_data_config(data_dir=None, export_config=True):
     return config
 
 
-def init_filters(data_dir=None, export_to_config=False):
+def init_filters(data_dir=None, export_config=False):
     """
     Initialize database filters
     :param data_dir: path to data directory
     :type data_dir: str or None
-    :param export_to_config: to export to config file
-    :type export_to_config: bool
+    :param export_config: to export to config file
+    :type export_config: bool
     :return: filters used by select_sub_data()
     :rtype: dict
     """
@@ -1388,7 +1388,7 @@ def init_filters(data_dir=None, export_to_config=False):
                 'subset_order': None,  # to give a custom order from plotting subset together
                 }
 
-    if export_to_config: 
+    if export_config: 
         if data_dir is None:
             raise Exception("ERROR: no data_dir given")
         else:
@@ -1406,7 +1406,7 @@ def make_all_config(data_dir=None, export_config=True):
     """
 
     data_config = make_data_config(data_dir=data_dir, export_config=export_config)
-    filters = init_filters(data_dir=data_dir, export_to_config=export_config)
+    filters = init_filters(data_dir=data_dir, export_config=export_config)
     traj_config = make_traj_config(data_dir=data_dir, export_config=export_config)
     map_config = make_map_config(data_dir=data_dir, export_config=export_config)
     plot_config = tpl.make_plot_config(data_dir=data_dir, export_config=export_config)

track_analyzer/scripts/analyze_maps.py

@@ -85,7 +85,20 @@ def map_analysis(data_dir, data=None, image=None, refresh=False, parallelize=Fal
     vector_mean = map_config["vector_mean"]
 
     # Filter data
-    filters = tpr.init_filters(data_dir=data_dir, export_to_config=True) if filters is None else filters
+    filters = tpr.init_filters(data_dir=data_dir, export_config=True) if filters is None else filters
+    # check that all keys are in filters, if not load default
+    filters_default = tpr.init_filters(data_dir=data_dir, export_config=False)
+    filters_default_dict = filters_default['filters_list'][0]
+    for k in filters_default.keys():
+        if k not in filters.keys():
+            filters[k] = filters_default[k]
+    # check all filter_subset
+    for i,filter_ in enumerate(filters['filters_list']): 
+        for k in filters_default_dict.keys():
+            if k not in filter_.keys():
+                filter_[k] = filters_default_dict[k]
+        filters['filters_list'][i] = filter_
+
     subset_analysis = filters['subset']  # how to deal with subsets
     filters_ = filters['filters_list']
     df = tpr.select_sub_data(df, filters=filters_)

track_analyzer/scripts/analyze_tracks.py

@@ -82,8 +82,23 @@ def traj_analysis(data_dir, data=None, image=None, refresh=False, parallelize=Fa
     voronoi_config = traj_config["voronoi_config"]
 
     # Filter data
-    filters = tpr.init_filters(data_dir=data_dir, export_to_config=False) if filters is None else filters
+    filters = tpr.init_filters(data_dir=data_dir, export_config=False) if filters is None else filters
+    # check that all keys are in filters, if not load default
+    filters_default = tpr.init_filters(data_dir=data_dir, export_config=False)
+    filters_default_dict = filters_default['filters_list'][0]
+    for k in filters_default.keys():
+        if k not in filters.keys():
+            filters[k] = filters_default[k]
+    # check all filter_subset
+    for i,filter_ in enumerate(filters['filters_list']): 
+        for k in filters_default_dict.keys():
+            if k not in filter_.keys():
+                filter_[k] = filters_default_dict[k]
+        filters['filters_list'][i] = filter_
+
     subset_analysis = filters['subset']  # how to deal with subsets
+    print(subset_analysis)
+    print(filters)
     filters_ = filters['filters_list']
     df = tpr.select_sub_data(df, filters=filters_)
     if subset_analysis == 'together':