Update app.py

app.py

@@ -25,7 +25,7 @@ def calculate_distances(coords):
     
     return distances, shortest_distances
 
-def plot_on_map(coords_list, shortest_distance, longest_shortest_distance, avg_distance, postcode_groups):
+def plot_on_map(coords_list, shortest_distance, longest_shortest_distance, avg_distance):
     all_coords = [coord for coords in coords_list for coord in coords]
     avg_lat = np.mean([coord[0] for coord in all_coords])
     avg_lon = np.mean([coord[1] for coord in all_coords])
@@ -64,20 +64,18 @@ def generate_map_with_stats(postcode_groups_input):
             coords = group['coords'].apply(lambda x: tuple(map(float, x.strip('()').split(',')))).tolist()
             coords_list.append(coords)
 
-    if coords_list:
-        all_distances = []
-        all_shortest_distances = []
-        for coords in coords_list:
-            distances, shortest_distances = calculate_distances(coords)
-            all_distances.extend(distances)
-            all_shortest_distances.extend(shortest_distances)
+    # Combine all coordinates into a single list
+    all_coords = [coord for coords in coords_list for coord in coords]
+
+    if all_coords:
+        distances, shortest_distances = calculate_distances(all_coords)
 
-        if all_shortest_distances:
-            shortest_distance = min(all_shortest_distances, key=lambda x: x[0])
-            longest_shortest_distance = max(all_shortest_distances, key=lambda x: x[0])
-            avg_distance = np.mean([dist[0] for dist in all_shortest_distances])
+        if shortest_distances:
+            shortest_distance = min(shortest_distances, key=lambda x: x[0])
+            longest_shortest_distance = max(shortest_distances, key=lambda x: x[0])
+            avg_distance = np.mean([dist[0] for dist in shortest_distances])
 
-            map_object = plot_on_map(coords_list, shortest_distance, longest_shortest_distance, avg_distance, postcode_groups)
+            map_object = plot_on_map([all_coords], shortest_distance, longest_shortest_distance, avg_distance)
 
             statistics = []
             for i, postcode_group in enumerate(postcode_groups):
@@ -100,5 +98,4 @@ iface = gr.Interface(
     article="\n\n\n*Store location data was last updated in February 2024.",
 )
 
-
 iface.launch(share=True)