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This commit is contained in:
Helldragon67 2025-01-23 16:22:41 +01:00
parent 577ee232fc
commit 259b0d36fd
5 changed files with 70 additions and 65 deletions

File diff suppressed because one or more lines are too long

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@ -25,8 +25,9 @@ class Overpass :
self.caching_strategy = CachingStrategy.use(caching_strategy, cache_dir=cache_dir)
@classmethod
def build_query(self, area: tuple, osm_types: osm_types,
selector: str, conditions=[], out='center'):
selector: str, conditions=[], out='center') -> str:
"""
Constructs a query string for the Overpass API to retrieve OpenStreetMap (OSM) data.
@ -83,7 +84,7 @@ class Overpass :
return query
def send_query(self, query: str) -> dict:
def send_query(self, query: str) -> ET:
"""
Sends the Overpass QL query to the Overpass API and returns the parsed JSON response.
@ -124,3 +125,47 @@ class Overpass :
except urllib.error.URLError as e:
raise ConnectionError(f"Error connecting to Overpass API: {e}") from e
def get_base_info(elem: ET.Element, osm_type: osm_types, with_name=False) :
"""
Extracts base information (coordinates, OSM ID, and optionally a name) from an OSM element.
This function retrieves the latitude and longitude coordinates, OSM ID, and optionally the name
of a given OpenStreetMap (OSM) element. It handles different OSM types (e.g., 'node', 'way') by
extracting coordinates either directly or from a center tag, depending on the element type.
Args:
elem (ET.Element): The XML element representing the OSM entity.
osm_type (str): The type of the OSM entity (e.g., 'node', 'way'). If 'node', the coordinates
are extracted directly from the element; otherwise, from the 'center' tag.
with_name (bool): Whether to extract and return the name of the element. If True, it attempts
to find the 'name' tag within the element and return its value. Defaults to False.
Returns:
tuple: A tuple containing:
- osm_id (str): The OSM ID of the element.
- coords (tuple): A tuple of (latitude, longitude) coordinates.
- name (str, optional): The name of the element if `with_name` is True; otherwise, not included.
"""
# 1. extract coordinates
if osm_type != 'node' :
center = elem.find('center')
lat = float(center.get('lat'))
lon = float(center.get('lon'))
else :
lat = float(elem.get('lat'))
lon = float(elem.get('lon'))
coords = tuple((lat, lon))
# 2. Extract OSM id
osm_id = elem.get('id')
# 3. Extract name if specified and return
if with_name :
name = elem.find("tag[@k='name']").get('v') if elem.find("tag[@k='name']") is not None else None
return osm_id, coords, name
else :
return osm_id, coords

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@ -6,7 +6,7 @@ import numpy as np
from sklearn.cluster import DBSCAN
from pydantic import BaseModel
from ..overpass.overpass import Overpass
from ..overpass.overpass import Overpass, get_base_info
from ..structs.landmark import Landmark
from .get_time_distance import get_distance
from ..constants import OSM_CACHE_DIR
@ -116,17 +116,11 @@ class ClusterManager:
points = []
for osm_type in osm_types :
for elem in result.findall(osm_type):
if osm_type != 'node' :
center = elem.find('center')
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)))
# Get coordinates and append them to the points list
_, coords = get_base_info(elem, osm_type)
if coords is not None :
points.append(coords)
if points :
self.all_points = np.array(points)
@ -263,32 +257,18 @@ class ClusterManager:
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
id, coords, name = get_base_info(elem, osm_type, with_name=True)
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'))
coords = tuple((lat, lon))
if coords is None :
if name is None or 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
osm_type = osm_type # Add type: 'way' or 'relation'
osm_id = id # Add OSM id
return Landmark(
name=new_name,

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@ -8,7 +8,7 @@ from ..structs.preferences import Preferences
from ..structs.landmark import Landmark
from .take_most_important import take_most_important
from .cluster_manager import ClusterManager
from ..overpass.overpass import Overpass
from ..overpass.overpass import Overpass, get_base_info
from ..constants import AMENITY_SELECTORS_PATH, LANDMARK_PARAMETERS_PATH, OPTIMIZER_PARAMETERS_PATH, OSM_CACHE_DIR
@ -239,28 +239,19 @@ class LandmarkManager:
landmarks = []
for osm_type in ['node', 'way', 'relation'] :
for elem in root.findall(osm_type):
name = elem.find("tag[@k='name']").get('v') if elem.find("tag[@k='name']") is not None else None
tags = elem.findall('tag')
if osm_type != 'node' :
center = elem.find('center')
lat = float(center.get('lat'))
lon = float(center.get('lon'))
coords = tuple((lat, lon))
else :
lat = float(elem.get('lat'))
lon = float(elem.get('lon'))
coords = tuple((lat, lon))
id, coords, name = get_base_info(elem, osm_type, with_name=True)
if name is None or coords is None :
continue
tags = elem.findall('tag')
# Convert this to Landmark object
landmark = Landmark(name=name,
type=landmarktype,
location=coords,
osm_id=elem.get('id'),
osm_id=id,
osm_type=osm_type,
attractiveness=0,
n_tags=len(tags))

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@ -2,7 +2,7 @@
import logging
import xml.etree.ElementTree as ET
from ..overpass.overpass import Overpass
from ..overpass.overpass import Overpass, get_base_info
from ..structs.landmark import Toilets
from ..constants import OSM_CACHE_DIR
@ -98,23 +98,12 @@ class ToiletsManager:
toilets_list = []
for osm_type in ['node', 'way', 'relation'] :
for elem in root.findall(osm_type):
center = elem.find('center')
# Extract the center latitude and longitude if available.
if osm_type != 'node' :
lat = float(center.get('lat'))
lon = float(center.get('lon'))
location = tuple((lat, lon))
else :
lat = float(elem.get('lat'))
lon = float(elem.get('lon'))
location = tuple((lat, lon))
if location is None :
# Get coordinates and append them to the points list
_, coords = get_base_info(elem, osm_type)
if coords is None :
continue
toilets = Toilets(location=location)
toilets = Toilets(location=coords)
# Extract tags as a dictionary
tags = {tag.get('k'): tag.get('v') for tag in elem.findall('tag')}