#!/usr/bin/env python # -*- coding: utf-8 -*- import networkx as nx import numpy as np import json import matplotlib.pyplot as plt
from shapely.geometry import asLineString, asMultiPoint def get_path(n0, n1): """If n0 and n1 are connected nodes in the graph, this function will return an array of point coordinates along the line linking these two nodes.""" return np.array(json.loads(nx_list_subgraph[n0][n1]['Json'])['coordinates']) def get_full_path(path): """ Create numpy array line result :param path: results of nx.shortest_path function :return: coordinate pairs along a path """ p_list = [] curp = None for i in range(len(path)-1): p = get_path(path[i], path[i+1]) if curp is None: curp = p if np.sum((p[0]-curp)**2) > np.sum((p[-1]-curp)**2): p = p[::-1, :] p_list.append(p) curp = p[-1] return np.vstack(p_list) def write_geojson(outfilename, indata): """ create GeoJSON file :param outfilename: name of output file :param indata: :return: a new GeoJSON file """ with open(outfilename, "w") as file_out: file_out.write(json.dumps(indata)) if __name__ == '__main__': # use Networkx to load a Noded shapefile # returns a graph where each node is a coordinate pair # and the edge is the line connecting the two nodes #点数据类转换为node，线转换为edge。坐标对作为keys，保持属性，线被简化为只保留起始点。 nx_load_shp = nx.read_shp("../geodata/shp/e01_network_lines_3857.shp") # A graph is not always connected, so we take the largest connected subgraph # by using the connected_component_subgraphs function. #获取连接子图 nx_list_subgraph = list(nx.connected_component_subgraphs(nx_load_shp.to_undirected()))[0] #获取所有节点 # get all the nodes in the network nx_nodes = np.array(nx_list_subgraph.nodes()) # output the nodes to a GeoJSON file to view in QGIS network_nodes = asMultiPoint(nx_nodes) write_geojson("../geodata/ch08_final_netx_nodes.geojson", network_nodes.__geo_interface__) # this number represents the nodes position # in the array to identify the node start_node_pos = 30 end_node_pos = 21 #计算最短路径 # Compute the shortest path. Dijkstra's algorithm. nx_short_path = nx.shortest_path(nx_list_subgraph, source=tuple(nx_nodes[start_node_pos]), target=tuple(nx_nodes[end_node_pos]), weight='distance') print(nx_short_path) # create numpy array of coordinates representing result path nx_array_path = get_full_path(nx_short_path) print("------------------------------------") print(nx_short_path) #将路径点连成线 # convert numpy array to Shapely Linestring out_shortest_path = asLineString(nx_array_path) write_geojson("../geodata/ch08_final_netx_sh_path.geojson", out_shortest_path.__geo_interface__)
nx.draw(nx_list_subgraph) #绘制网络G
#plt.savefig("ba.png") #输出方式1: 将图像存为一个png格式的图片文件
plt.show()
