Используя Формула Хаверсин , чтобы найти ближайшую точку (например, город) на основе широты и долготы.
def dist_between_two_lat_lon(*args):
from math import asin, cos, radians, sin, sqrt
lat1, lat2, long1, long2 = map(radians, args)
dist_lats = abs(lat2 - lat1)
dist_longs = abs(long2 - long1)
a = sin(dist_lats/2)**2 + cos(lat1) * cos(lat2) * sin(dist_longs/2)**2
c = asin(sqrt(a)) * 2
radius_earth = 6378 # the "Earth radius" R varies from 6356.752 km at the poles to 6378.137 km at the equator.
return c * radius_earth
def find_closest_lat_lon(data, v):
try:
return min(data, key=lambda p: dist_between_two_lat_lon(v['lat'],v['lon'],p['lat'],p['lon']))
except TypeError:
print('Not a list or not a number.')
# city = {'lat_key': value, 'lon_key': value} # type:dict()
new_york = {'lat': 40.712776, 'lon': -74.005974}
washington = {'lat': 47.751076, 'lon': -120.740135}
san_francisco = {'lat': 37.774929, 'lon': -122.419418}
city_list = [new_york, washington, san_francisco]
city_to_find = {'lat': 29.760427, 'lon': -95.369804} # Houston
print(find_closest_lat_lon(city_list, city_to_find))
Какие выходы:
{'lat': 47.751076, 'lon': -120.740135} # Corresponds to Washington
Давайте Предположим, вы получили четыре json ответа из карты и сохранили их в списке:
json_answers = list() # = []
json_answers.append({'type': 'FeatureCollection',
'query': [32.12, 54.21],
'features': [{'id': 'country.10008046970720960',
'type': 'Feature',
'place_type': ['country'],
'relevance': 1,
'properties': {'short_code': 'ru', 'wikidata': 'Q159'},
'text': 'Russia',
'place_name': 'Russia',
'bbox': [19.608673, 41.185353, 179.9, 81.961618],
'center': [37.61667, 55.75],
'geometry': {'type': 'Point', 'coordinates': [37.61667, 55.75]}}],
'attribution': 'NOTICE: ...'})
# I changed only the 'coordinates' value for this example
json_answers.append({'type': 'FeatureCollection',
'query': [32.12, 54.21],
'features': [{'id': 'country.10008046970720960',
'type': 'Feature',
'place_type': ['country'],
'relevance': 1,
'properties': {'short_code': 'ru', 'wikidata': 'Q159'},
'text': 'Russia',
'place_name': 'Russia',
'bbox': [19.608673, 41.185353, 179.9, 81.961618],
'center': [37.61667, 55.75],
'geometry': {'type': 'Point', 'coordinates': [38.21667, 56.15]}}],
'attribution': 'NOTICE: ...'})
# I changed only the 'coordinates' value for this example
json_answers.append({'type': 'FeatureCollection',
'query': [32.12, 54.21],
'features': [{'id': 'country.10008046970720960',
'type': 'Feature',
'place_type': ['country'],
'relevance': 1,
'properties': {'short_code': 'ru', 'wikidata': 'Q159'},
'text': 'Russia',
'place_name': 'Russia',
'bbox': [19.608673, 41.185353, 179.9, 81.961618],
'center': [37.61667, 55.75],
'geometry': {'type': 'Point', 'coordinates': [33.21667, 51.15]}}],
'attribution': 'NOTICE: ...'})
# The last answer is "null"
json_answers.append({'type': 'FeatureCollection',
'query': [0, 0],
'features': [],
'attribution': 'NOTICE: ...'})
coord_list = []
for answer in json_answers:
if answer['features']: # check if ['features'] is not empty
# I'm not sure if it's [lat, lon] or [lon, lat] (you can verify it on mapbox)
print(f"Coordinates in [lat, lon]: {answer['features'][0]['geometry']['coordinates']}")
lat = answer['features'][0]['geometry']['coordinates'][0]
lon = answer['features'][0]['geometry']['coordinates'][1]
temp_dict = {'lat': lat, 'lon': lon}
coord_list.append(temp_dict)
print(f"coord_list = {coord_list}")
point_to_find = {'lat': 37.41667, 'lon': 55.05} # Houston
print(f"point_to_find = {point_to_find}")
print(f"find_closest_lat_lon = {find_closest_lat_lon(coord_list, point_to_find)}")
Что дает:
{'lat': 47.751076, 'lon': -120.740135}
Coordinates in [lat, lon]: [37.61667, 55.75]
Coordinates in [lat, lon]: [38.21667, 56.15]
Coordinates in [lat, lon]: [33.21667, 51.15]
coord_list = [{'lat': 37.61667, 'lon': 55.75}, {'lat': 38.21667, 'lon': 56.15}, {'lat': 33.21667, 'lon': 51.15}]
point_to_find = {'lat': 37.41667, 'lon': 55.05}
find_closest_lat_lon = {'lat': 38.21667, 'lon': 56.15}