def get_sbwstops(o_lat, o_lng, d_lat, d_lng, dis):
#设置最远阈值1000米范围内
o_dmin = [dis, None]
d_dmin = [dis, None]
ominlat, omaxlat, ominlng, omaxlng = get_area(o_lat, o_lng, dis / 1000)
dminlat, dmaxlat, dminlng, dmaxlng = get_area(d_lat, d_lng, dis / 1000)
for key in sbwstation:
[t_lat, t_lng] = sbwstation[key].get_location()
if t_lat > ominlat and t_lat < omaxlat and t_lng > ominlng and t_lng < omaxlng:
o_d = get_distance(o_lat, o_lng, sbwstation[key].get_location()[0],
sbwstation[key].get_location()[1])
o_dmin = ([o_d, key] if o_d < o_dmin[0] else o_dmin)
if t_lat > dminlat and t_lat < dmaxlat and t_lng > dminlng and t_lng < dmaxlng:
d_d = get_distance(d_lat, d_lng, sbwstation[key].get_location()[0],
sbwstation[key].get_location()[1])
d_dmin = ([d_d, key] if d_d < d_dmin[0] else d_dmin)
return o_dmin, d_dmin
lat = sdata[key][k][i]['latitude']
lng = sdata[key][k][i]['longitude']
if lat < 100:
location = [lat, lng]
else:
location = [lng, lat]
sline = copy.deepcopy(stopline[name])
ydstation[name] = Station(id, name, location, sline)
num += 1
# 站点半径500米内其他站点定义为周边站点【0】，获取周边站点集合并添加到对应站点类中
nearby_stops = {}
for i in stop:
nearby_stops[i] = []
[c_lat, c_lng] = ydstation[i].get_location()
minlat, maxlat, minlng, maxlng = get_area(c_lat, c_lng, 0.5)
n_stops = {}
for j in stop:
[t_lat, t_lng] = ydstation[j].get_location()
if t_lat > minlat and t_lat < maxlat and t_lng > minlng and t_lng < maxlng:
n_stops[j] = get_distance(c_lat, c_lng, t_lat, t_lng)
n_stops.pop(i)
nearby_stops[i] = copy.deepcopy(n_stops)
for key in ydstation:
stopsdict = {0: copy.deepcopy(nearby_stops[key])}
ydstation[key].set_stops(stopsdict)
# DICT SBWSTATION
# 将获取到的地铁json站点数据整理成站点类的形式，存在key为地铁站点id，value为站点类的字典中
sbwstation = {}
for i in range(len(sbw_sdata)):