import networkx as nx import math from itertools import tee from numpy import Inf, Infinity, inf from database.database import DB import pandas as pd from haversine import haversine import time import pandas as pd import os paths= os.getcwd() def dist(a, b): (x1, y1) = a (x2, y2) = b return ((x1 - x2) ** 2 + (y1 - y2) ** 2) ** 0.5 def swith_xy(tuples): x,y=tuples return (y,x) def pairwise( iterable ): """Returns an iterable access binary tuple s -> (s0,s1), (s1,s2), (s2, s3), ...""" a, b = tee( iterable ) next(b, None) return zip(a, b) class path_finder(): def __init__(self): start_time=time.time() self.db=DB() self.G=nx.read_gpickle(paths + '\\navigation_model\\OSM_gpickle.gpickle') print("done") print(time.time()-start_time) def get_trip(self,dest1,dest2): start_time=time.time() dest1=swith_xy(self.db.db_get_dest(dest1)) dest2=swith_xy(self.db.db_get_dest(dest2)) value=0.0001 start_near_nodes=[] while start_near_nodes == []: value=value*10 start_near_nodes=self.db.db_get_near_node(dest1[1],dest1[0],value) else: start_near_nodes=self.db.db_get_near_node(dest1[1],dest1[0],value) nn_start = None nn_end = None start_delta = float("inf") end_delta = float("inf") for n in start_near_nodes: s_dist = haversine(dest1, n) if s_dist < start_delta : nn_start = n start_delta = s_dist value=0.0001 end_near_nodes=[] while end_near_nodes==[]: value=value*10 self.db.db_get_near_node(dest2[1],dest2[0],value) end_near_nodes=self.db.db_get_near_node(dest2[1],dest2[0],value) for n in end_near_nodes: e_dist = haversine(dest2, n) if e_dist < end_delta : nn_end = n end_delta = e_dist path = list(nx.astar_path(self.G,nn_start,nn_end,heuristic=dist,weight='length')) return path def get_dest(self, dest1): dest1=swith_xy(self.db.db_get_address(dest1)) return dest1 db=DB() df = pd.read_csv('D:\\takensoft\\project2\\경산 길찾기\\경산시_체크.csv',encoding='euc-kr') li_start=[] li_dest1=[] for i in range(len(df)): try: print(i) dest1=df['start'][i] li_dest1.append(dest1) dest1=swith_xy(db.db_get_dest(dest1)) value=0.0001 start_near_nodes=[] while start_near_nodes == []: value=value*10 start_near_nodes=db.db_get_near_node(dest1[1],dest1[0],value) nn_start = None start_delta = float("inf") for n in start_near_nodes: s_dist = haversine(dest1, n) if s_dist < start_delta : nn_start = n start_delta = s_dist li_start.append(nn_start) except: continue df_check=pd.DataFrame({'start':li_dest1,'시작지점':li_start}) df_check.to_csv('test.csv',encoding='euc-kr') ''' df=pd.read_csv('D:\\takensoft\\project2\\경산 길찾기\\경산시.csv',encoding='euc-kr') p=path_finder() li_path=[] for i in range(len(df)): try: if i%100 ==0: print(i) df2=pd.DataFrame(li_path) df2.to_csv(f'D:\\takensoft\\project2\\경산 길찾기\\길찾기 결과{i}.csv',encoding='euc-kr') li_path=[] start=df['start'][i] end=df['end'][i] li_path.append(p.get_trip(start,end)) except: continue li_start_x = [] li_start_y = [] li_end_x = [] li_end_y = [] db=DB() #df.to_csv('D:\\takensoft\\project2\\경산 길찾기\\길찾기 결과.csv',encoding='euc-kr') df=pd.read_csv('D:\\takensoft\\project2\\경산 길찾기\\경산시.csv',encoding='euc-kr') for i in range(len(df)): li_start_x.append(db.db_get_dest(df['start'][i])[0]) li_start_y.append(db.db_get_dest(df['start'][i])[1]) li_end_x.append(db.db_get_dest(df['end'][i])[0]) li_end_y.append([db.db_get_dest(df['end'][i])[1]]) df2 = pd.DataFrame({'start_point_x':li_start_x,'start_point_y':li_start_y,'end_point_x':li_end_x,'end_point_y':li_end_y}) df2.to_csv('D:\\takensoft\\project2\\경산 길찾기\\출발지도착지좌표.csv',encoding='euc-kr') '''