def google_walking_driving_path(start, dest, city_id, dist):
start_map = start.split('#')[-1]
dest_map = dest.split('#')[-1]
real_start_map = formatCoor(start_map)
real_dest_map = formatCoor(dest_map)
ssdb_key_walking = "###".join(["walking", real_start_map, real_dest_map])
ssdb_key_driving = "###".join(["driving", real_start_map, real_dest_map])
if dist < 3000:
path_walking = ssdb.request("get", [ssdb_key_walking])
path_walking_str = str(path_walking)
if path_walking_str == "d None None" or path_walking_str == "not_found None None":
path_driving = ssdb.request("get", [ssdb_key_driving])
path_driving_str = str(path_driving)
#google步行和驾车数据都为空，拉一条直线路径
if path_driving_str == "d None None" or path_driving_str == "not_found None None":
return line_walk_path(start, dest, city_id, dist)
else:
return path_driving_str[8:]
else:
return path_walking_str[8:]
else:
path_driving = ssdb.request("get", [ssdb_key_driving])
path_driving_str = str(path_driving)
if path_driving_str == "d None None" or path_driving_str == "not_found None None":
path_walking = ssdb.request("get", [ssdb_key_walking])
path_walking_str = str(path_walking)
#google步行和驾车数据都为空时，拉一条直线距离
if path_walking_str == "d None None" or path_walking_str == "not_found None None":
return line_walk_path(start, dest, city_id, dist)
else:
return path_walking_str[8:]
else:
return path_driving_str[8:]
def google_walk_path(start, dest):
#start_list = start.split('#')
#dest_list = dest.split('#')
#real_start_map = formatCoor(start_list[len(start_list) - 1])
#real_dest_map = formatCoor(dest_list[len(dest_list) - 1])
real_start_map = formatCoor(start.split('#')[-1])
real_dest_map = formatCoor(dest.split('#')[-1])
ssdb_key = "###".join(['walking', real_start_map, real_dest_map])
path = ssdb.request('get', [ssdb_key])
return path
def google_driving_path(start, dest):
start_map = start.split('#')[-1]
dest_map = dest.split('#')[-1]
real_start_map = formatCoor(start_map)
real_dest_map = formatCoor(dest_map)
ssdb_key_driving = "###".join(["driving", real_start_map, real_dest_map])
path_driving = ssdb.request("get", [ssdb_key_driving])
path_driving_str = str(path_driving)
if path_driving_str == "d None None" or path_driving_str == "not_found None None":
return ""
return path_driving_str[8:]
def find_path_sub(start, dest, start_type, dest_type, start_nearest_station,
dest_nearest_station, city_id):
#start_list = start.split('#')
#dest_list = dest.split('#')
#start_poi_map = start_list[len(start_list) - 1]
#dest_poi_map = dest_list[len(dest_list) - 1]
start_poi_map = start.split('#')[-1]
dest_poi_map = dest.split('#')[-1]
strKey_list = []
#起始和终止poi点附近所有交通站点的组合，方便从redis数据库中批量读取数据
for start_station in start_nearest_station:
start_map = start_station[0].split('#')[-1]
for dest_station in dest_nearest_station:
dest_map = dest_station[0].split('#')[-1]
if start_map != dest_map:
strKey = start_map.strip() + "###" + dest_map.strip() + "@0@0"
strKey_list.append(strKey)
#批量读取交通路线数据
strValue_list = r0.mget(strKey_list)
path_list = {}
#读取的数据拼接成字典形式
for index in range(len(strValue_list)):
path_list[strKey_list[index]] = strValue_list[index]
min_score = sys.maxint
res_path = {}
start_path_str_res = ""
dest_path_str_res = ""
path_str_res = ""
start_t = time.time()
#批量获取起始poi点到附近交通站点的Google交通数据（步行数据和驾车数据）
start_walking_ssdbkey_list = []
start_driving_ssdbkey_list = []
for start_station in start_nearest_station:
start_map = start_station[0].split('#')[-1]
real_start_map = formatCoor(start_poi_map)
real_dest_map = formatCoor(start_map)
ssdb_key_walking = "###".join(
["walking", real_start_map, real_dest_map])
ssdb_key_driving = "###".join(
["driving", real_start_map, real_dest_map])
start_driving_ssdbkey_list.append(ssdb_key_driving)
start_walking_ssdbkey_list.append(ssdb_key_walking)
start_walking_path_str = str(
ssdb.request('multi_get', start_walking_ssdbkey_list))
start_driving_path_str = str(
ssdb.request('multi_get', start_driving_ssdbkey_list))
start_walking_path_str = start_walking_path_str[8:]
start_driving_path_str = start_driving_path_str[8:]
start_walking_path_dic = eval(start_walking_path_str)
start_driving_path_dic = eval(start_driving_path_str)
start_driving_path_dic = start_driving_path_dic["items"]
start_walking_path_dic = start_walking_path_dic["items"]
#批量获取终止poi点到附近交通站点的Google交通数据（步行数据和驾车数据）
dest_walking_ssdbkey_list = []
dest_driving_ssdbkey_list = []
for dest_station in dest_nearest_station:
dest_map = dest_station[0].split('#')[-1]
real_start_map = formatCoor(dest_map)
real_dest_map = formatCoor(dest_poi_map)
ssdb_key_walking = "###".join(
["walking", real_start_map, real_dest_map])
ssdb_key_driving = "###".join(
["driving", real_start_map, real_dest_map])
dest_walking_ssdbkey_list.append(ssdb_key_walking)
dest_driving_ssdbkey_list.append(ssdb_key_driving)
dest_walking_path_str = str(
ssdb.request('multi_get', dest_walking_ssdbkey_list))
dest_driving_path_str = str(
ssdb.request('multi_get', dest_driving_ssdbkey_list))
dest_walking_path_str = dest_walking_path_str[8:]
dest_driving_path_str = dest_driving_path_str[8:]
dest_walking_path_dic = eval(dest_walking_path_str)
dest_driving_path_dic = eval(dest_driving_path_str)
dest_walking_path_dic = dest_walking_path_dic["items"]
dest_driving_path_dic = dest_driving_path_dic["items"]
end_t = time.time()
#print "ssdb mutli_get : ",end_t - start_t
#拼接Google获取的交通数据和交通站点的交通数据进行拼接
start_t = time.time()
for start_station in start_nearest_station:
start_map = start_station[0].split('#')[-1]
start_real_start_map = formatCoor(start_poi_map)
start_real_dest_map = formatCoor(start_map)
start_dis = CoordDist.getDistance(
start_poi_map.split(',') + start_map.split(','))
start_path = ""
#两点之间的直线距离小于3000m时，优先选择Google步行数据，如果Google步行数据为空，则选择驾车数据，如果驾车数据也为空，则在两点之间拉一条直线
if start_dis <= 3000:
ssdb_key_walking = "###".join(
["walking", start_real_start_map, start_real_dest_map])
start_path = start_walking_path_dic.get(ssdb_key_walking)
if start_path is None:
ssdb_key_driving = "###".join(
["driving", start_real_start_map, start_real_dest_map])
start_path = start_driving_path_dic.get(ssdb_key_driving)
if start_path is None:
start_path = line_walk_path(start, start_station[0],
city_id, start_dis)
else:
ssdb_key_driving = "###".join(
["driving", start_real_start_map, start_real_dest_map])
start_path = start_driving_path_dic.get(ssdb_key_driving)
if start_path is None:
ssdb_key_walking = "###".join(
["walking", start_real_start_map, start_real_dest_map])
start_path = start_walking_path_dic.get(ssdb_key_walking)
if start_path is None:
start_path = line_walk_path(start, start_station[0],
city_id, start_dis)
#start_path = google_walking_driving_path(start_poi_map,start_map,start_dis)
#google返回的数据为空，则在两个poi点之间拉一条直线
#if start_path == "":
# start_path = line_walk_path(start,start_station[0],city_id,start_dis)
for dest_station in dest_nearest_station:
dest_map = dest_station[0].split('#')[-1]
dest_real_start_map = formatCoor(dest_map)
dest_real_dest_map = formatCoor(dest_poi_map)
dest_dis = CoordDist.getDistance(
dest_poi_map.split(',') + dest_map.split(','))
dest_path = ""
if dest_dis <= 3000:
ssdb_key_walking = "###".join(
["walking", dest_real_start_map, dest_real_dest_map])
dest_path = dest_walking_path_dic.get(ssdb_key_walking)
if dest_path is None:
ssdb_key_driving = "###".join(
["driving", dest_real_start_map, dest_real_dest_map])
dest_path = dest_driving_path_dic.get(ssdb_key_driving)
if dest_path is None:
dest_path = line_walk_path(dest_station[0], dest,
city_id, dest_dis)
else:
ssdb_key_driving = "###".join(
["driving", dest_real_start_map, dest_real_dest_map])
dest_path = dest_driving_path_dic.get(ssdb_key_driving)
if dest_path is None:
ssdb_key_walking = "###".join(
["walking", dest_real_start_map, dest_real_dest_map])
dest_path = dest_walking_path_dic.get(ssdb_key_walking)
if dest_path is None:
dest_path = line_walk_path(dest_station[0], dest,
city_id, dest_dis)
#dest_path = google_walking_driving_path(dest_map,dest_poi_map,dest_dis)
#google返回的数据为空，则在两个poi点之间拉一条直线
#if dest_path == "":
# dest_path = line_walk_path(dest_station[0],dest,city_id,dest_dis)
if start_map != dest_map:
strKey = start_map.strip() + "###" + dest_map.strip() + "@0@0"
#pathStr = r0.get(strKey)
pathStr = path_list[strKey]
#两个交通站点之间没有计算出路径信息，则选择google步行数据
if pathStr is None:
path_dis = CoordDist.getDistance(
start_map.split(',') + dest_map.split(','))
pathStr = google_walking_driving_path(
start_station[0], dest_station[0], city_id, path_dis)
start_path_dic = eval(start_path)
dest_path_dic = eval(dest_path)
try:
path_dic = eval(pathStr)
except:
print strKey
tmp_score = int(path_dic["score"])
if start_type.strip() == "1":
tmp_score += int(start_path_dic["time"])
if dest_type.strip() == "1":
tmp_score += int(dest_path_dic["time"])
#path_dic = combine_path(start_path,dest_path,start_type,dest_type,pathStr)
if tmp_score < min_score:
start_path_str_res = start_path
dest_path_str_res = dest_path
path_str_res = pathStr
min_score = tmp_score
end_t = time.time()
#print "for time : ",end_t - start_t
res_path = combine_path(start_path_str_res, dest_path_str_res, start_type,
dest_type, path_str_res)
res_path["start_id"] = start
res_path["dest_id"] = dest
res_path["start_map"] = start.split('#')[-1]
res_path["dest_map"] = dest.split("#")[-1]
#print res_path
return str(res_path)
def find_path_sub_0_1(start, dest, dest_nearest_station, city_id, pathes_dic):
start_map = start.split('#')[-1]
dest_poi_map = dest.split('#')[-1]
strKey_list = []
#起始和终止poi点附近所有交通站点的组合，方便从redis数据库中批量读取数据
for dest_station in dest_nearest_station:
dest_map = dest_station[0].split('#')[-1]
if start_map != dest_map:
strKey = start_map.strip() + "###" + dest_map.strip() + "@0@0"
strKey_list.append(strKey)
#批量读取交通路线数据
strValue_list = r0.mget(strKey_list)
path_list = {}
#读取的数据拼接成字典形式
for index in range(len(strValue_list)):
path_list[strKey_list[index]] = strValue_list[index]
min_score = sys.maxint
res_path = {}
dest_path_str_res = ""
path_str_res = ""
#批量获取终止poi点到附近交通站点的Google交通数据（步行数据和驾车数据）
dest_walking_ssdbkey_list = []
dest_driving_ssdbkey_list = []
for dest_station in dest_nearest_station:
dest_map = dest_station[0].split('#')[-1]
real_start_map = formatCoor(dest_map)
real_dest_map = formatCoor(dest_poi_map)
ssdb_key_walking = "###".join(
["walking", real_start_map, real_dest_map])
ssdb_key_driving = "###".join(
["driving", real_start_map, real_dest_map])
dest_walking_ssdbkey_list.append(ssdb_key_walking)
dest_driving_ssdbkey_list.append(ssdb_key_driving)
dest_walking_path_str = str(
ssdb.request('multi_get', dest_walking_ssdbkey_list))
dest_driving_path_str = str(
ssdb.request('multi_get', dest_driving_ssdbkey_list))
dest_walking_path_str = dest_walking_path_str[8:]
dest_driving_path_str = dest_driving_path_str[8:]
dest_walking_path_dic = eval(dest_walking_path_str)
dest_driving_path_dic = eval(dest_driving_path_str)
dest_walking_path_dic = dest_walking_path_dic["items"]
dest_driving_path_dic = dest_driving_path_dic["items"]
#拼接Google获取的交通数据和交通站点的交通数据进行拼接
for dest_station in dest_nearest_station:
dest_map = dest_station[0].split('#')[-1]
dest_real_start_map = formatCoor(dest_map)
dest_real_dest_map = formatCoor(dest_poi_map)
dest_dis = CoordDist.getDistance(
dest_poi_map.split(',') + dest_map.split(','))
dest_path = ""
if dest_dis <= 3000:
ssdb_key_walking = "###".join(
["walking", dest_real_start_map, dest_real_dest_map])
dest_path = dest_walking_path_dic.get(ssdb_key_walking)
if dest_path is None:
ssdb_key_driving = "###".join(
["driving", dest_real_start_map, dest_real_dest_map])
dest_path = dest_driving_path_dic.get(ssdb_key_driving)
if dest_path is None:
dest_path = line_walk_path(dest_station[0], dest, city_id,
dest_dis)
else:
ssdb_key_driving = "###".join(
["driving", dest_real_start_map, dest_real_dest_map])
dest_path = dest_driving_path_dic.get(ssdb_key_driving)
if dest_path is None:
ssdb_key_walking = "###".join(
["walking", dest_real_start_map, dest_real_dest_map])
dest_path = dest_walking_path_dic.get(ssdb_key_walking)
if dest_path is None:
dest_path = line_walk_path(dest_station[0], dest, city_id,
dest_dis)
dest_path_dic = eval(dest_path)
if start_map != dest_map:
strKey = start_map.strip() + "###" + dest_map.strip() + "@0@0"
pathStr = path_list[strKey]
#两个交通站点之间没有计算出路径信息，则选择google步行数据
if pathStr is None:
path_dis = CoordDist.getDistance(
start_map.split(',') + dest_map.split(','))
pathStr = google_walking_driving_path(start_station[0],
dest_station[0], city_id,
path_dis)
path_dic = eval(pathStr)
tmp_score = int(path_dic["score"]) + int(dest_path_dic["time"])
if tmp_score < min_score:
dest_path_str_res = dest_path
path_str_res = pathStr
min_score = tmp_score
else:
tmp_score = int(dest_path_dic["time"])
if tmp_score < min_score:
dest_path_str_res = dest_path
path_str_res = ""
min_score = tmp_score
if path_str_res == "":
res_path = eval(dest_path_str_res)
else:
res_path = combine_path("", dest_path_str_res, "0", "1", path_str_res)
res_path["start_id"] = start
res_path["dest_id"] = dest
res_path["start_map"] = start.split('#')[-1]
res_path["dest_map"] = dest.split("#")[-1]
str_res_key = start_map + "###" + dest_poi_map + "@0@0"
pathes_dic[str_res_key] = str(res_path)
#print res_path
return str(res_path)
def find_path_sub_1_0(start, start_nearest_station, dest, city_id, pathes_dic):
start_poi_map = start.split('#')[-1]
dest_poi_map = dest.split('#')[-1]
min_score = sys.maxint
res_path = {}
start_path_str_res = ""
path_str_res = ""
#批量获取起始poi点到附近交通站点的Google交通数据（步行数据和驾车数据）
start_walking_ssdbkey_list = []
start_driving_ssdbkey_list = []
for start_station in start_nearest_station:
start_map = start_station[0].split('#')[-1]
real_start_map = formatCoor(start_poi_map)
real_dest_map = formatCoor(start_map)
ssdb_key_walking = "###".join(
["walking", real_start_map, real_dest_map])
ssdb_key_driving = "###".join(
["driving", real_start_map, real_dest_map])
start_driving_ssdbkey_list.append(ssdb_key_driving)
start_walking_ssdbkey_list.append(ssdb_key_walking)
start_walking_path_str = str(
ssdb.request('multi_get', start_walking_ssdbkey_list))
start_driving_path_str = str(
ssdb.request('multi_get', start_driving_ssdbkey_list))
start_walking_path_str = start_walking_path_str[8:]
start_driving_path_str = start_driving_path_str[8:]
start_walking_path_dic = eval(start_walking_path_str)
start_driving_path_dic = eval(start_driving_path_str)
start_driving_path_dic = start_driving_path_dic["items"]
start_walking_path_dic = start_walking_path_dic["items"]
#拼接Google获取的交通数据和交通站点的交通数据进行拼接
for start_station in start_nearest_station:
start_map = start_station[0].split('#')[-1]
start_real_start_map = formatCoor(start_poi_map)
start_real_dest_map = formatCoor(start_map)
start_dis = CoordDist.getDistance(
start_poi_map.split(',') + start_map.split(','))
start_path = ""
#两点之间的直线距离小于3000m时，优先选择Google步行数据，如果Google步行数据为空，则选择驾车数据，如果驾车数据也为空，则在两点之间拉一条直线
if start_dis <= 3000:
ssdb_key_walking = "###".join(
["walking", start_real_start_map, start_real_dest_map])
start_path = start_walking_path_dic.get(ssdb_key_walking)
if start_path is None:
ssdb_key_driving = "###".join(
["driving", start_real_start_map, start_real_dest_map])
start_path = start_driving_path_dic.get(ssdb_key_driving)
if start_path is None:
start_path = line_walk_path(start, start_station[0],
city_id, start_dis)
else:
ssdb_key_driving = "###".join(
["driving", start_real_start_map, start_real_dest_map])
start_path = start_driving_path_dic.get(ssdb_key_driving)
if start_path is None:
ssdb_key_walking = "###".join(
["walking", start_real_start_map, start_real_dest_map])
start_path = start_walking_path_dic.get(ssdb_key_walking)
if start_path is None:
start_path = line_walk_path(start, start_station[0],
city_id, start_dis)
dest_map = dest.split('#')[-1]
start_path_dic = eval(start_path)
if start_map != dest_map:
strKey = start_map + "###" + dest_map + "@0@0"
pathStr = pathes_dic[strKey]
path_dic = eval(pathStr)
tmp_score = int(path_dic["time"]) + int(start_path_dic["time"])
if tmp_score < min_score:
start_path_str_res = start_path
path_str_res = pathStr
min_score = tmp_score
else:
tmp_score = int(start_path_dic["time"])
if tmp_score < min_score:
start_path_str_res = start_path
path_str_res = ""
min_score = tmp_score
if path_str_res == "":
res_path = eval(start_path_str_res)
else:
res_path = combine_path(start_path_str_res, "", "1", "0", path_str_res)
res_path["start_id"] = start
res_path["dest_id"] = dest
res_path["start_map"] = start.split('#')[-1]
res_path["dest_map"] = dest.split("#")[-1]
return str(res_path)