根据地理参考多边形裁剪 networkx 图

Question

我是运行一个循环，它为 GeoDataFrames（城市）列表的每一行（社区）计算 networkx.classes.multidigraph.MultiDiGraph。然后它为每一行计算一些统计数据并将文件写出到磁盘。问题是循环计算起来非常长，因为图形是为每一行计算的。

我想加快循环的方法是计算整个 GeoDataFrame 的图形，然后将图形裁剪到每一行（每一行都有一个多边形）。您可以使用 geopandas.clip 为 GeoSeries 执行此操作。然而，对于 networkx 图，似乎不存在等同于 geopandas.clip 的东西。

有谁知道剪辑 networkx 图的方法吗？
或者，还有哪些其他方法可以加快我的循环。
注意：如果我可以将 networkx 图转换为 pandas 对象，则剪裁将起作用。不幸的是，我认为当图形转换为 pandas 对象时，不可能保留 osmnx 作用的属性。如果我错了，请这样说。

这是我的初始代码：

import osmnx as ox
import pandas as pd
import geopandas as gpd
import os

path="C:/folder/"
files=[os.path.join(path, f) for f in os.listdir(path)]

for i in range(0,2):
    city=gpd.read_file(files[i])
    circ=[]

    for i in range(0,181):
        graph_for_row=ox.graph_from_polygon(city.geometry[i])
        #above is the long command
        stat = ox.basic_stats(graph_for_row)
        circ.append(stat['circuity_avg'])

    circ=pd.Series(circ)
    merged.append(pd.concat([city, circ], axis=1))

for i in (range(0,len(merged))):
    with open(geofiles[i], 'w') as f:
        f.write(merged[i].to_json())

这是我的目标新循环：

clipped_graph=[]

for i in range(0,2):
    city=gpd.read_file(files[i])
    whole_city=city.unary_union
    graph=ox.graph_from_polygon(whole_city)
    clipped_graph.append(gpd.clip(graph, city.geometry))#this line 
    #does not work since 'graph' is a networkx object, not
    #a GeoDataFrame or GeoSeries
    circ=[]

    for i in range(0,181)
        stat = ox.basic_stats(clipped_graph[i])
        circ.append(stat['circuity_avg'])

    circ=pd.Series(circ)
    merged.append(pd.concat([city, circ], axis=1))

for i in (range(0,len(merged))):
    with open(geofiles[i], 'w') as f:
        f.write(merged[i].to_json())

Answer 1

您可以使用您的个人多边形（在空间上）与图形节点相交，然后使用这些节点产生 subgraph。 MWE:

import osmnx as ox
ox.config(use_cache=True, log_console=True)

# load a shapefile of polygons as geodataframe using geopandas
# here i just get 3 cities from OSM to make example reproducible without a shapefile
places = ['Cudahy, CA, USA', 'Bell, CA, USA', 'Maywood, CA, USA']
gdf = ox.gdf_from_places(places)

# get a graph of the union of their boundaries, then extract nodes as geodataframe
G = ox.graph_from_polygon(gdf.unary_union, network_type='drive')
nodes = ox.graph_to_gdfs(G, edges=False)

# for each city polygon, find intersecting nodes then induce subgraph
for polygon in gdf['geometry']:
    intersecting_nodes = nodes[nodes.intersects(polygon)].index
    G_sub = G.subgraph(intersecting_nodes)
    fig, ax = ox.plot_graph(G_sub)

根据地理参考多边形裁剪 networkx 图

Clipping a networkx graph according to georeferenced polygon

python

pandas

networkx

geopandas

osmnx