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fixed cluster names

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This commit is contained in:
Helldragon67 2025-02-11 07:34:50 +01:00
parent 9002483036
commit 81330e5eb3
9 changed files with 34 additions and 30 deletions

12
backend/report.html

File diff suppressed because one or more lines are too long

3
backend/src/main.py

@ -130,11 +130,12 @@ def new_trip(preferences: Preferences,
logger.debug(f'First stage optimization\t: {round(t_first_stage,3)} seconds')
logger.debug(f'Second stage optimization\t: {round(t_second_stage,3)} seconds')
logger.info(f'Total computation time\t: {round(t_first_stage + t_second_stage,3)} seconds')
linked_tour = LinkedLandmarks(refined_tour)
# upon creation of the trip, persistence of both the trip and its landmarks is ensured.
trip = Trip.from_linked_landmarks(linked_tour, cache_client)
logger.info(f'Generated a trip of {trip.total_time} minutes with {len(refined_tour)} landmarks in {round(t_generate_landmarks + t_first_stage + t_second_stage,3)} seconds.')
logger.debug('Detailed trip :\n\t' + '\n\t'.join(f'{landmark}' for landmark in refined_tour))
background_tasks.add_task(fill_cache)

2
backend/src/optimization/optimizer.py

@ -594,7 +594,7 @@ class Optimizer:
status = pl.LpStatus[prob.status]
solution = [pl.value(var) for var in x] # The values of the decision variables (will be 0 or 1)
self.logger.debug("First results are out. Looking out for circles and correcting.")
self.logger.debug("First results are out. Looking out for circles and correcting...")
# Raise error if no solution is found. FIXME: for now this throws the internal server error
if status != 'Optimal' :

4
backend/src/overpass/overpass.py

@ -52,7 +52,7 @@ class Overpass :
# Retrieve cached data and identify missing cache entries
cached_responses, non_cached_cells = self._retrieve_cached_data(overlapping_cells, osm_types, selector, conditions, out)
self.logger.info(f'Cache hit for {len(overlapping_cells)-len(non_cached_cells)}/{len(overlapping_cells)} quadrants.')
self.logger.debug(f'Cache hit for {len(overlapping_cells)-len(non_cached_cells)}/{len(overlapping_cells)} quadrants.')
# If there is no missing data, return the cached responses after filtering.
if not non_cached_cells :
@ -61,6 +61,7 @@ class Overpass :
# If there is no cached data, fetch all from Overpass.
elif not cached_responses :
query_str = Overpass.build_query(bbox, osm_types, selector, conditions, out)
self.logger.debug(f'Query string: {query_str}')
return self.fetch_data_from_api(query_str)
# Hybrid cache: some data from Overpass, some data from cache.
@ -68,6 +69,7 @@ class Overpass :
# Resize the bbox for smaller search area and build new query string.
non_cached_bbox = Overpass._get_non_cached_bbox(non_cached_cells, bbox)
query_str = Overpass.build_query(non_cached_bbox, osm_types, selector, conditions, out)
self.logger.debug(f'Query string: {query_str}')
non_cached_responses = self.fetch_data_from_api(query_str)
return Overpass._filter_landmarks(cached_responses, bbox) + non_cached_responses

7
backend/src/parameters/landmark_parameters.yaml

@ -1,12 +1,11 @@
max_bbox_side: 4000 #m
radius_close_to: 50
church_coeff: 0.55
nature_coeff: 1.4
church_coeff: 0.75
nature_coeff: 1.6
overall_coeff: 10
tag_exponent: 1.15
image_bonus: 1.1
viewpoint_bonus: 5
viewpoint_bonus: 10
wikipedia_bonus: 1.25
name_bonus: 3
N_important: 60
pay_bonus: -1

2
backend/src/parameters/optimizer_parameters.yaml

@ -5,5 +5,5 @@ max_landmarks: 10
max_landmarks_refiner: 20
overshoot: 0.0016
time_limit: 1
gap_rel: 0.05
gap_rel: 0.025
max_iter: 40

4
backend/src/tests/test_main.py

@ -31,9 +31,9 @@ def test_turckheim(client, request): # pylint: disable=redefined-outer-name
"shopping": {"type": "shopping", "score": 0},
"max_time_minute": duration_minutes,
"detour_tolerance_minute": 0},
# "start": [48.084588, 7.280405]
"start": [48.084588, 7.280405]
# "start": [45.74445023349939, 4.8222687890538865]
"start": [45.75156398104873, 4.827154464827647]
# "start": [45.75156398104873, 4.827154464827647]
}
)
result = response.json()

23
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,

7
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