fixed cluster names

backend/src/utils/cluster_manager.py

@@ -1,6 +1,6 @@
 """Find clusters of interest to add more general areas of visit to the tour."""
 import logging
-from typing import Literal
+from typing import Literal, Tuple
 
 import numpy as np
 from sklearn.cluster import DBSCAN
@@ -33,7 +33,7 @@ class Cluster(BaseModel):
     """
     type: Literal['street', 'area']
     importance: int
-    centroid: tuple
+    centroid: Tuple[float, float]
     # start: Optional[list] = None      # for later use if we want to have streets as well
     # end: Optional[list] = None
 
@@ -178,11 +178,12 @@ class ClusterManager:
 
             # Calculate the centroid as the mean of the points
             centroid = np.mean(current_cluster, axis=0)
+            centroid = tuple((round(centroid[0], 7), round(centroid[1], 7)))
 
             if self.cluster_type == 'shopping' :
-                score = len(current_cluster)*2
+                score = len(current_cluster)*3
             else :
-                score = len(current_cluster)*8
+                score = len(current_cluster)*15
             locations.append(Cluster(
                 type='area',
                 centroid=centroid,
@@ -215,7 +216,7 @@ class ClusterManager:
         """
 
         # Define the bounding box for a given radius around the coordinates
-        bbox = create_bbox(cluster.centroid, 1000)
+        bbox = create_bbox(cluster.centroid, 300)
         
         # Query neighborhoods and shopping malls
         selectors = ['"place"~"^(suburb|neighborhood|neighbourhood|quarter|city_block)$"']
@@ -223,10 +224,10 @@ class ClusterManager:
         if self.cluster_type == 'shopping' :
             selectors.append('"shop"="mall"')
             new_name = 'Shopping Area'
-            t = 40
+            t = 30
         else :
             new_name = 'Neighborhood'
-            t = 15
+            t = 20
 
         min_dist = float('inf')
         osm_id = 0
@@ -238,7 +239,7 @@ class ClusterManager:
                 result = self.overpass.send_query(bbox = bbox,
                                                   osm_types = osm_types,
                                                   selector = sel,
-                                                  out = 'ids center'
+                                                  out = 'ids center tags'
                                                   )
             except Exception as e:
                 self.logger.error(f"Error fetching clusters: {e}")
@@ -259,9 +260,9 @@ class ClusterManager:
                 d = get_distance(cluster.centroid, coords)
                 if  d < min_dist :
                     min_dist = d
-                    new_name = name
-                    osm_type = osm_type     # Add type: 'way' or 'relation'
-                    osm_id = id             # Add OSM id
+                    new_name = name         # add name
+                    osm_type = osm_type     # add type: 'way' or 'relation'
+                    osm_id = id             # add OSM id
 
         return Landmark(
             name=new_name,

backend/src/utils/landmarks_manager.py

@@ -39,7 +39,6 @@ class LandmarkManager:
             self.overall_coeff = parameters['overall_coeff']
             self.tag_exponent = parameters['tag_exponent']
             self.image_bonus = parameters['image_bonus']
-            self.name_bonus = parameters['name_bonus']
             self.wikipedia_bonus = parameters['wikipedia_bonus']
             self.viewpoint_bonus = parameters['viewpoint_bonus']
             self.pay_bonus = parameters['pay_bonus']
@@ -147,6 +146,8 @@ class LandmarkManager:
             score *= self.wikipedia_bonus
         if landmark.is_place_of_worship :
             score *= self.church_coeff
+        if landmark.is_viewpoint :
+            score *= self.viewpoint_bonus
         if landmarktype == 'nature' :
             score *= self.nature_coeff
 
@@ -201,7 +202,7 @@ class LandmarkManager:
 
             return_list += self._to_landmarks(result, landmarktype, preference_level)
 
-        self.logger.debug(f"Fetched {len(return_list)} landmarks of type {landmarktype} in {bbox}")
+        # self.logger.debug(f"Fetched {len(return_list)} landmarks of type {landmarktype} in {bbox}")
 
         return return_list
 
@@ -267,7 +268,7 @@ class LandmarkManager:
                     landmark.image_url = value
                 if key == 'website' :
                     landmark.website_url = value
-                if key == 'place_of_worship' :
+                if value == 'place_of_worship' :
                     landmark.is_place_of_worship = True
                 if key == 'wikipedia' :
                     landmark.wiki_url = value