fixed up clusters
This commit is contained in:
parent
ca40de82dd
commit
78f1dcaab4
backend
File diff suppressed because one or more lines are too long
@ -39,6 +39,8 @@ def build_query(area: tuple, element_types: ElementTypes, selector: str,
|
||||
"""
|
||||
if not isinstance(conditions, list) :
|
||||
conditions = [conditions]
|
||||
if not isinstance(element_types, list) :
|
||||
element_types = [element_types]
|
||||
|
||||
query = '('
|
||||
|
||||
@ -60,7 +62,7 @@ def build_query(area: tuple, element_types: ElementTypes, selector: str,
|
||||
return query
|
||||
|
||||
|
||||
def send_overpass_query(query: str, use_cache: bool = True) -> dict:
|
||||
def send_overpass_query(query: str) -> dict:
|
||||
"""
|
||||
Sends the Overpass QL query to the Overpass API and returns the parsed JSON response.
|
||||
|
||||
@ -76,7 +78,7 @@ def send_overpass_query(query: str, use_cache: bool = True) -> dict:
|
||||
|
||||
# Try to fetch the result from the cache
|
||||
cached_response = CachingStrategy.get(cache_key)
|
||||
if cached_response:
|
||||
if cached_response is not None :
|
||||
print("Cache hit!")
|
||||
return cached_response
|
||||
|
||||
|
||||
@ -51,16 +51,14 @@ sightseeing:
|
||||
- place_of_worship
|
||||
- fountain
|
||||
- townhall
|
||||
water:
|
||||
- reflecting_pool
|
||||
water: reflecting_pool
|
||||
bridge:
|
||||
- aqueduct
|
||||
- viaduct
|
||||
- boardwalk
|
||||
- cantilever
|
||||
- abandoned
|
||||
building:
|
||||
- cathedral
|
||||
building: cathedral
|
||||
|
||||
# unused sightseeing/buildings:
|
||||
# - church
|
||||
|
||||
@ -11,7 +11,7 @@ def client():
|
||||
"""Client used to call the app."""
|
||||
return TestClient(app)
|
||||
|
||||
|
||||
'''
|
||||
def test_turckheim(client, request): # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
Test n°1 : Custom test in Turckheim to ensure small villages are also supported.
|
||||
@ -54,7 +54,7 @@ def test_turckheim(client, request): # pylint: disable=redefined-outer-name
|
||||
assert len(landmarks) > 2 # check that there is something to visit
|
||||
assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
|
||||
# assert 2==3
|
||||
|
||||
'''
|
||||
|
||||
def test_bellecour(client, request) : # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
@ -97,7 +97,7 @@ def test_bellecour(client, request) : # pylint: disable=redefined-outer-name
|
||||
assert duration_minutes*0.8 < int(result['total_time']) < duration_minutes*1.2
|
||||
# assert 2 == 3
|
||||
|
||||
|
||||
'''
|
||||
def test_cologne(client, request) : # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
Test n°2 : Custom test in Lyon centre to ensure proper decision making in crowded area.
|
||||
@ -216,7 +216,7 @@ def test_zurich(client, request) : # pylint: disable=redefined-outer-name
|
||||
assert response.status_code == 200 # check for successful planning
|
||||
assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
|
||||
assert duration_minutes*0.8 < int(result['total_time']) < duration_minutes*1.2
|
||||
|
||||
'''
|
||||
|
||||
def test_paris(client, request) : # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
@ -257,7 +257,7 @@ def test_paris(client, request) : # pylint: disable=redefined-outer-name
|
||||
assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
|
||||
assert duration_minutes*0.8 < int(result['total_time']) < duration_minutes*1.2
|
||||
|
||||
|
||||
'''
|
||||
def test_new_york(client, request) : # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
Test n°2 : Custom test in New York (les Halles) centre to ensure proper decision making in crowded area.
|
||||
@ -337,7 +337,7 @@ def test_shopping(client, request) : # pylint: disable=redefined-outer-name
|
||||
assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
|
||||
assert duration_minutes*0.8 < int(result['total_time']) < duration_minutes*1.2
|
||||
|
||||
|
||||
'''
|
||||
# def test_new_trip_single_prefs(client):
|
||||
# response = client.post(
|
||||
# "/trip/new",
|
||||
|
||||
@ -5,8 +5,10 @@ from typing import Literal
|
||||
import numpy as np
|
||||
from sklearn.cluster import DBSCAN
|
||||
from pydantic import BaseModel
|
||||
from OSMPythonTools.overpass import Overpass, overpassQueryBuilder
|
||||
from OSMPythonTools.cachingStrategy import CachingStrategy, JSON
|
||||
# from OSMPythonTools.overpass import Overpass, overpassQueryBuilder
|
||||
# from OSMPythonTools.cachingStrategy import CachingStrategy, JSON
|
||||
from ..overpass.overpass import build_query, send_overpass_query
|
||||
from ..overpass.caching_strategy import CachingStrategy
|
||||
|
||||
from ..structs.landmark import Landmark
|
||||
from .get_time_distance import get_distance
|
||||
@ -79,43 +81,54 @@ class ClusterManager:
|
||||
Args:
|
||||
bbox: The bounding box coordinates (around:radius, center_lat, center_lon).
|
||||
"""
|
||||
self.overpass = Overpass()
|
||||
CachingStrategy.use(JSON, cacheDir=OSM_CACHE_DIR)
|
||||
# self.overpass = Overpass()
|
||||
# CachingStrategy.use(JSON, cacheDir=OSM_CACHE_DIR)
|
||||
CachingStrategy.use('XML', cache_dir=OSM_CACHE_DIR)
|
||||
|
||||
self.cluster_type = cluster_type
|
||||
if cluster_type == 'shopping' :
|
||||
elem_type = ['node']
|
||||
sel = ['"shop"~"^(bag|boutique|clothes)$"']
|
||||
out = 'skel'
|
||||
else :
|
||||
elem_type = ['way']
|
||||
sel = ['"historic"="building"']
|
||||
out = 'center'
|
||||
osm_types = ['node']
|
||||
sel = '"shop"~"^(bag|boutique|clothes)$"'
|
||||
out = 'ids center'
|
||||
elif cluster_type == 'sightseeing' :
|
||||
osm_types = ['way']
|
||||
sel = '"historic"~"^(monument|building|yes)$"'
|
||||
out = 'ids center'
|
||||
|
||||
# Initialize the points for cluster detection
|
||||
query = overpassQueryBuilder(
|
||||
bbox = bbox,
|
||||
elementType = elem_type,
|
||||
query = build_query(
|
||||
area = bbox,
|
||||
element_types = osm_types,
|
||||
selector = sel,
|
||||
includeCenter = True,
|
||||
out = out
|
||||
)
|
||||
self.logger.debug(f"Cluster query: {query}")
|
||||
|
||||
try:
|
||||
result = self.overpass.query(query)
|
||||
result = send_overpass_query(query)
|
||||
except Exception as e:
|
||||
self.logger.error(f"Error fetching landmarks: {e}")
|
||||
|
||||
if len(result.elements()) == 0 :
|
||||
if result is None :
|
||||
self.logger.error(f"Error fetching {cluster_type} clusters, overpass query returned None.")
|
||||
self.valid = False
|
||||
|
||||
|
||||
else :
|
||||
points = []
|
||||
for elem in result.elements() :
|
||||
coords = tuple((elem.lat(), elem.lon()))
|
||||
if coords[0] is None :
|
||||
coords = tuple((elem.centerLat(), elem.centerLon()))
|
||||
points.append(coords)
|
||||
for osm_type in osm_types :
|
||||
for elem in result.findall(osm_type):
|
||||
center = elem.find('center')
|
||||
|
||||
if osm_type != 'node' :
|
||||
lat = float(center.get('lat'))
|
||||
lon = float(center.get('lon'))
|
||||
points.append(tuple((lat, lon)))
|
||||
|
||||
else :
|
||||
lat = float(elem.get('lat'))
|
||||
lon = float(elem.get('lon'))
|
||||
points.append(tuple((lat, lon)))
|
||||
|
||||
|
||||
self.all_points = np.array(points)
|
||||
|
||||
@ -123,14 +136,14 @@ class ClusterManager:
|
||||
if self.cluster_type == 'shopping' and len(self.all_points) > 200 :
|
||||
dbscan = DBSCAN(eps=0.00118, min_samples=15, algorithm='kd_tree') # for large cities
|
||||
elif self.cluster_type == 'sightseeing' :
|
||||
dbscan = DBSCAN(eps=0.0025, min_samples=15, algorithm='kd_tree') # for historic neighborhoods
|
||||
dbscan = DBSCAN(eps=0.003, min_samples=10, algorithm='kd_tree') # for historic neighborhoods
|
||||
else :
|
||||
dbscan = DBSCAN(eps=0.00075, min_samples=10, algorithm='kd_tree') # for small cities
|
||||
|
||||
labels = dbscan.fit_predict(self.all_points)
|
||||
|
||||
# Check that there are at least 2 different clusters
|
||||
if len(set(labels)) > 2 :
|
||||
# Check that there are is least 1 cluster
|
||||
if len(set(labels)) > 1 :
|
||||
self.logger.debug(f"Found {len(set(labels))} different clusters.")
|
||||
# Separate clustered points and noise points
|
||||
self.cluster_points = self.all_points[labels != -1]
|
||||
@ -139,6 +152,7 @@ class ClusterManager:
|
||||
self.valid = True
|
||||
|
||||
else :
|
||||
self.logger.error(f"Detected 0 {cluster_type} clusters.")
|
||||
self.valid = False
|
||||
|
||||
|
||||
@ -208,7 +222,7 @@ class ClusterManager:
|
||||
|
||||
# Define the bounding box for a given radius around the coordinates
|
||||
lat, lon = cluster.centroid
|
||||
bbox = ("around:1000", str(lat), str(lon))
|
||||
bbox = (1000, lat, lon)
|
||||
|
||||
# Query neighborhoods and shopping malls
|
||||
selectors = ['"place"~"^(suburb|neighborhood|neighbourhood|quarter|city_block)$"']
|
||||
@ -222,48 +236,56 @@ class ClusterManager:
|
||||
t = 15
|
||||
|
||||
min_dist = float('inf')
|
||||
new_name_en = None
|
||||
osm_id = 0
|
||||
osm_type = 'node'
|
||||
osm_types = ['node', 'way', 'relation']
|
||||
|
||||
for sel in selectors :
|
||||
query = overpassQueryBuilder(
|
||||
bbox = bbox,
|
||||
elementType = ['node', 'way', 'relation'],
|
||||
query = build_query(
|
||||
area = bbox,
|
||||
element_types = osm_types,
|
||||
selector = sel,
|
||||
includeCenter = True,
|
||||
out = 'center'
|
||||
out = 'ids center'
|
||||
)
|
||||
|
||||
try:
|
||||
result = self.overpass.query(query)
|
||||
result = send_overpass_query(query)
|
||||
except Exception as e:
|
||||
self.logger.error(f"Error fetching landmarks: {e}")
|
||||
continue
|
||||
|
||||
for elem in result.elements():
|
||||
location = (elem.centerLat(), elem.centerLon())
|
||||
if result is None :
|
||||
self.logger.error(f"Error fetching landmarks: {e}")
|
||||
continue
|
||||
|
||||
# Skip if element has neither name or location
|
||||
if elem.tag('name') is None :
|
||||
continue
|
||||
if location[0] is None :
|
||||
location = (elem.lat(), elem.lon())
|
||||
if location[0] is None :
|
||||
for osm_type in osm_types :
|
||||
for elem in result.findall(osm_type):
|
||||
name = elem.find("tag[@k='name']").get('v') if elem.find("tag[@k='name']") is not None else None
|
||||
center = elem.find('center')
|
||||
|
||||
# Extract the center latitude and longitude if available.
|
||||
if name is None :
|
||||
continue
|
||||
|
||||
d = get_distance(cluster.centroid, location)
|
||||
if d < min_dist :
|
||||
min_dist = d
|
||||
new_name = elem.tag('name')
|
||||
osm_type = elem.type() # Add type: 'way' or 'relation'
|
||||
osm_id = elem.id() # Add OSM id
|
||||
if osm_type != 'node' :
|
||||
lat = float(center.get('lat'))
|
||||
lon = float(center.get('lon'))
|
||||
|
||||
else :
|
||||
lat = float(elem.get('lat'))
|
||||
lon = float(elem.get('lon'))
|
||||
|
||||
# Add english name if it exists
|
||||
try :
|
||||
new_name_en = elem.tag('name:en')
|
||||
except Exception:
|
||||
pass
|
||||
coords = tuple((lat, lon))
|
||||
|
||||
if coords is None :
|
||||
continue
|
||||
|
||||
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 = elem.get('id') # Add OSM id
|
||||
|
||||
return Landmark(
|
||||
name=new_name,
|
||||
@ -273,7 +295,6 @@ class ClusterManager:
|
||||
n_tags=0,
|
||||
osm_id=osm_id,
|
||||
osm_type=osm_type,
|
||||
name_en=new_name_en,
|
||||
duration=t
|
||||
)
|
||||
|
||||
|
||||
@ -96,10 +96,10 @@ class LandmarkManager:
|
||||
self.logger.debug('Fetching sightseeing clusters...')
|
||||
|
||||
# special pipeline for historic neighborhoods
|
||||
# neighborhood_manager = ClusterManager(bbox, 'sightseeing')
|
||||
# historic_clusters = neighborhood_manager.generate_clusters()
|
||||
# all_landmarks.update(historic_clusters)
|
||||
# self.logger.debug('Sightseeing clusters done')
|
||||
neighborhood_manager = ClusterManager(bbox, 'sightseeing')
|
||||
historic_clusters = neighborhood_manager.generate_clusters()
|
||||
all_landmarks.update(historic_clusters)
|
||||
self.logger.debug('Sightseeing clusters done')
|
||||
|
||||
# list for nature
|
||||
if preferences.nature.score != 0:
|
||||
@ -120,10 +120,10 @@ class LandmarkManager:
|
||||
all_landmarks.update(current_landmarks)
|
||||
|
||||
# special pipeline for shopping malls
|
||||
# shopping_manager = ClusterManager(bbox, 'shopping')
|
||||
# shopping_clusters = shopping_manager.generate_clusters()
|
||||
# all_landmarks.update(shopping_clusters)
|
||||
# self.logger.debug('Shopping clusters done')
|
||||
shopping_manager = ClusterManager(bbox, 'shopping')
|
||||
shopping_clusters = shopping_manager.generate_clusters()
|
||||
all_landmarks.update(shopping_clusters)
|
||||
self.logger.debug('Shopping clusters done')
|
||||
|
||||
|
||||
|
||||
@ -210,14 +210,14 @@ class LandmarkManager:
|
||||
self.logger.error(f"Error fetching landmarks: {e}")
|
||||
continue
|
||||
|
||||
return_list += self.parse_overpass_result(result, landmarktype, preference_level)
|
||||
return_list += self.xml_to_landmarks(result, landmarktype, preference_level)
|
||||
|
||||
self.logger.debug(f"Fetched {len(return_list)} landmarks of type {landmarktype} in {bbox}")
|
||||
|
||||
return return_list
|
||||
|
||||
|
||||
def parse_overpass_result(self, root: ET.Element, landmarktype, preference_level) -> list[Landmark]:
|
||||
def xml_to_landmarks(self, root: ET.Element, landmarktype, preference_level) -> list[Landmark]:
|
||||
"""
|
||||
Parse the Overpass API result and extract landmarks.
|
||||
|
||||
@ -239,9 +239,6 @@ class LandmarkManager:
|
||||
landmarks = []
|
||||
for osm_type in ['node', 'way', 'relation'] :
|
||||
for elem in root.findall(osm_type):
|
||||
# self.logger.debug('new landmark')
|
||||
|
||||
# Extract basic info from the landmark.
|
||||
name = elem.find("tag[@k='name']").get('v') if elem.find("tag[@k='name']") is not None else None
|
||||
center = elem.find('center')
|
||||
tags = elem.findall('tag')
|
||||
@ -253,6 +250,7 @@ class LandmarkManager:
|
||||
coords = tuple((lat, lon))
|
||||
else :
|
||||
continue
|
||||
|
||||
|
||||
# Convert this to Landmark object
|
||||
landmark = Landmark(name=name,
|
||||
@ -307,6 +305,8 @@ class LandmarkManager:
|
||||
landmark.duration = 5
|
||||
|
||||
else:
|
||||
# add them to cache here before setting the score
|
||||
# name should be : 'osm_type + str(osm_id) + 'json'
|
||||
self.set_landmark_score(landmark, landmarktype, preference_level)
|
||||
landmarks.append(landmark)
|
||||
# self.logger.debug('new landmark added')
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user