在 Python 中迭代 OSMNX 中的等时线
Iterating over an isochrone in OSMNX in Python
我正在尝试使用 Python based on this example 中的 OSMNX 遍历一些多边形，但我遇到了输出问题。
设置：
import geopandas as gpd
import matplotlib.pyplot as plt
import networkx as nx
import osmnx as ox
from descartes import PolygonPatch
from shapely.geometry import Point, LineString, Polygon
ox.config(log_console=True, use_cache=True)
ox.__version__
# get one color for each isochrone
iso_colours = ox.get_colors(n=len(trip_times), cmap='Reds', start=0.3, return_hex=True)
#info for later on
network_type = 'walk'
trip_times = [5, 10] #in minutes
travel_speed = 4.8 #walking speed in km/hour
metres_per_minute = travel_speed * 1000 / 60 #km per hour to m per minute
# isochrone function
def make_iso_polys(G, edge_buff=25, node_buff=50, infill=False):
isochrone_polys = []
for trip_time in sorted(trip_times, reverse=True):
subgraph = nx.ego_graph(G, centre_node, radius=trip_time, distance='time')
node_points = [Point((data['x'], data['y'])) for node, data in subgraph.nodes(data=True)]
nodes_gdf = gpd.GeoDataFrame({'id': subgraph.nodes()}, geometry=node_points)
nodes_gdf = nodes_gdf.set_index('id')
edge_lines = []
for n_fr, n_to in subgraph.edges():
f = nodes_gdf.loc[n_fr].geometry
t = nodes_gdf.loc[n_to].geometry
edge_lines.append(LineString([f,t]))
n = nodes_gdf.buffer(node_buff).geometry
e = gpd.GeoSeries(edge_lines).buffer(edge_buff).geometry
all_gs = list(n) + list(e)
new_iso = gpd.GeoSeries(all_gs).unary_union
# try to fill in surrounded areas so shapes will appear solid and blocks without white space inside them
if infill:
new_iso = Polygon(new_iso.exterior)
isochrone_polys.append(new_iso)
return isochrone_polys
# the area
mv = ox.graph_from_bbox(-37.705, -37.796, 144.949, 144.84, network_type='walk')
mv_projected = ox.project_graph(mv)
ox.plot_graph(mv_projected)
multiple_coords = ((-37.773981, 144.915669),
(-37.765443, 144.863070),
(-37.736089, 144.888972),
(-37.764914, 144.924148),
(-37.788513, 144.930533))
问题出在哪里。我添加了一些额外的文本来跟踪代码中发生的事情：
# test function to do multiple ones
def iterate_multiple_coords(the_coordinates):
for i in the_coordinates:
centre_node = ox.get_nearest_node(mv, (i[0], i[1]))
print("starting" + str(i)) # to check
# add an edge attribute for time in minutes required to traverse each edge
for u, v, k, data in mv_projected.edges(data=True, keys=True):
data['time'] = data['length'] / metres_per_minute
# make the polygons
isochrone_polys_iter = make_iso_polys(mv_projected, edge_buff=25, node_buff=0, infill=True)
print("done " + str([i])) # to check
poly_list.append(isochrone_polys_iter)
print("appended " + str([i])) # to check
return(poly_list)
#list of shapely objects
test = iterate_multiple_coords(multiple_coords)
这似乎可行，但是当您查看已创建的多边形时，它们只是其中两个的副本。他们应该都是不同的。
for i in test:
print(i[0].area)
print(i[1].area)
只生产副本：
[<shapely.geometry.polygon.Polygon object at 0x00000252EED81048>, <shapely.geometry.polygon.Polygon object at 0x0000025299DCD7B8>]
1221891.0262004482
278954.2285476034
[<shapely.geometry.polygon.Polygon object at 0x000002529A0FF978>, <shapely.geometry.polygon.Polygon object at 0x00000252F0884978>]
1170723.0839951886
254020.00263692273
我该如何解决这个问题？谢谢。
试图重现这个问题，我运行陷入了两个错误。解决这些似乎会产生正确的结果。首先，make_iso_polys 还需要有 centre_node 作为参数：
def make_iso_polys(G, centre_node, edge_buff=25, node_buff=50, infill=False):
isochrone_polys = []
for trip_time in sorted(trip_times, reverse=True):
subgraph = nx.ego_graph(G, centre_node, radius=trip_time, distance='time')
node_points = [Point((data['x'], data['y'])) for node, data in subgraph.nodes(data=True)]
nodes_gdf = gpd.GeoDataFrame({'id': subgraph.nodes()}, geometry=node_points)
nodes_gdf = nodes_gdf.set_index('id')
edge_lines = []
for n_fr, n_to in subgraph.edges():
f = nodes_gdf.loc[n_fr].geometry
t = nodes_gdf.loc[n_to].geometry
edge_lines.append(LineString([f,t]))
n = nodes_gdf.buffer(node_buff).geometry
e = gpd.GeoSeries(edge_lines).buffer(edge_buff).geometry
all_gs = list(n) + list(e)
new_iso = gpd.GeoSeries(all_gs).unary_union
# try to fill in surrounded areas so shapes will appear solid and blocks without white space inside them
if infill:
new_iso = Polygon(new_iso.exterior)
isochrone_polys.append(new_iso)
return isochrone_polys
我怀疑这就是您的问题所在。如果您在某个时候在函数外部定义了 centre_node，那么 make_iso_poly 将在名称空间中进行搜索，直到找到一个值。
我也 运行 遇到错误 iterate_multiple_coords 没有要追加的列表，这很容易解决：
def iterate_multiple_coords(the_coordinates):
poly_list = []
for i in the_coordinates:
centre_node = ox.get_nearest_node(mv, (i[0], i[1]))
print("starting" + str(i)) # to check
# add an edge attribute for time in minutes required to traverse each edge
for u, v, k, data in mv_projected.edges(data=True, keys=True):
data['time'] = data['length'] / metres_per_minute
# make the polygons
isochrone_polys_iter = make_iso_polys(mv_projected,
centre_node,
edge_buff=25,
node_buff=0,
infill=True)
print("done " + str([i])) # to check
poly_list.append(isochrone_polys_iter)
print("appended " + str([i])) # to check
return(poly_list)
我尝试使用更多输出进行测试以确定多边形不同：
#list of shapely objects
test = iterate_multiple_coords(multiple_coords)
for i, poly in enumerate(test):
print(i)
print(poly[0].bounds)
print(poly[0].area)
print(poly[1].bounds)
print(poly[1].area)
这个returns对我来说
0
(315719.9722479802, -4183576.0970487385, 317146.7585685815, -4182104.248355794)
1064783.069852857
(316092.45915179665, -4183138.881268308, 316857.3685328224, -4182352.8318315353)
207488.55915115002
1
(311160.15906794026, -4182601.4787744572, 312318.75050440413, -4181146.474157421)
844021.6754682651
(311491.4241338904, -4182296.4498064136, 312171.21314883756, -4181535.6374544636)
181959.15194429446
2
(313349.77854383545, -4179191.5691777603, 314706.9086066517, -4177874.3106440073)
697618.2735243046
(313611.9777962584, -4178837.4315966303, 314316.9596420839, -4178365.0333478907)
105808.08447317046
3
(316506.3163716192, -4182533.536447418, 317712.9680439883, -4181044.336753285)
1042931.7802330595
(316764.0345564607, -4182162.9997046595, 317463.6017386513, -4181398.2886200016)
276870.23606513516
4
(317045.2449636515, -4185110.519037448, 318554.4721278832, -4183677.93438998)
1170827.5838636972
(317408.8052150706, -4184702.3494480574, 318143.3573653238, -4184063.5647333027)
253939.04383932063
我正在尝试使用 Python based on this example 中的 OSMNX 遍历一些多边形，但我遇到了输出问题。
设置：
import geopandas as gpd
import matplotlib.pyplot as plt
import networkx as nx
import osmnx as ox
from descartes import PolygonPatch
from shapely.geometry import Point, LineString, Polygon
ox.config(log_console=True, use_cache=True)
ox.__version__
# get one color for each isochrone
iso_colours = ox.get_colors(n=len(trip_times), cmap='Reds', start=0.3, return_hex=True)
#info for later on
network_type = 'walk'
trip_times = [5, 10] #in minutes
travel_speed = 4.8 #walking speed in km/hour
metres_per_minute = travel_speed * 1000 / 60 #km per hour to m per minute
# isochrone function
def make_iso_polys(G, edge_buff=25, node_buff=50, infill=False):
isochrone_polys = []
for trip_time in sorted(trip_times, reverse=True):
subgraph = nx.ego_graph(G, centre_node, radius=trip_time, distance='time')
node_points = [Point((data['x'], data['y'])) for node, data in subgraph.nodes(data=True)]
nodes_gdf = gpd.GeoDataFrame({'id': subgraph.nodes()}, geometry=node_points)
nodes_gdf = nodes_gdf.set_index('id')
edge_lines = []
for n_fr, n_to in subgraph.edges():
f = nodes_gdf.loc[n_fr].geometry
t = nodes_gdf.loc[n_to].geometry
edge_lines.append(LineString([f,t]))
n = nodes_gdf.buffer(node_buff).geometry
e = gpd.GeoSeries(edge_lines).buffer(edge_buff).geometry
all_gs = list(n) + list(e)
new_iso = gpd.GeoSeries(all_gs).unary_union
# try to fill in surrounded areas so shapes will appear solid and blocks without white space inside them
if infill:
new_iso = Polygon(new_iso.exterior)
isochrone_polys.append(new_iso)
return isochrone_polys
# the area
mv = ox.graph_from_bbox(-37.705, -37.796, 144.949, 144.84, network_type='walk')
mv_projected = ox.project_graph(mv)
ox.plot_graph(mv_projected)
multiple_coords = ((-37.773981, 144.915669),
(-37.765443, 144.863070),
(-37.736089, 144.888972),
(-37.764914, 144.924148),
(-37.788513, 144.930533))
问题出在哪里。我添加了一些额外的文本来跟踪代码中发生的事情：
# test function to do multiple ones
def iterate_multiple_coords(the_coordinates):
for i in the_coordinates:
centre_node = ox.get_nearest_node(mv, (i[0], i[1]))
print("starting" + str(i)) # to check
# add an edge attribute for time in minutes required to traverse each edge
for u, v, k, data in mv_projected.edges(data=True, keys=True):
data['time'] = data['length'] / metres_per_minute
# make the polygons
isochrone_polys_iter = make_iso_polys(mv_projected, edge_buff=25, node_buff=0, infill=True)
print("done " + str([i])) # to check
poly_list.append(isochrone_polys_iter)
print("appended " + str([i])) # to check
return(poly_list)
#list of shapely objects
test = iterate_multiple_coords(multiple_coords)
这似乎可行，但是当您查看已创建的多边形时，它们只是其中两个的副本。他们应该都是不同的。
for i in test:
print(i[0].area)
print(i[1].area)
只生产副本：
[<shapely.geometry.polygon.Polygon object at 0x00000252EED81048>, <shapely.geometry.polygon.Polygon object at 0x0000025299DCD7B8>]
1221891.0262004482
278954.2285476034
[<shapely.geometry.polygon.Polygon object at 0x000002529A0FF978>, <shapely.geometry.polygon.Polygon object at 0x00000252F0884978>]
1170723.0839951886
254020.00263692273
我该如何解决这个问题？谢谢。
试图重现这个问题，我运行陷入了两个错误。解决这些似乎会产生正确的结果。首先，make_iso_polys 还需要有 centre_node 作为参数：
def make_iso_polys(G, centre_node, edge_buff=25, node_buff=50, infill=False):
isochrone_polys = []
for trip_time in sorted(trip_times, reverse=True):
subgraph = nx.ego_graph(G, centre_node, radius=trip_time, distance='time')
node_points = [Point((data['x'], data['y'])) for node, data in subgraph.nodes(data=True)]
nodes_gdf = gpd.GeoDataFrame({'id': subgraph.nodes()}, geometry=node_points)
nodes_gdf = nodes_gdf.set_index('id')
edge_lines = []
for n_fr, n_to in subgraph.edges():
f = nodes_gdf.loc[n_fr].geometry
t = nodes_gdf.loc[n_to].geometry
edge_lines.append(LineString([f,t]))
n = nodes_gdf.buffer(node_buff).geometry
e = gpd.GeoSeries(edge_lines).buffer(edge_buff).geometry
all_gs = list(n) + list(e)
new_iso = gpd.GeoSeries(all_gs).unary_union
# try to fill in surrounded areas so shapes will appear solid and blocks without white space inside them
if infill:
new_iso = Polygon(new_iso.exterior)
isochrone_polys.append(new_iso)
return isochrone_polys
我怀疑这就是您的问题所在。如果您在某个时候在函数外部定义了 centre_node，那么 make_iso_poly 将在名称空间中进行搜索，直到找到一个值。
我也 运行 遇到错误 iterate_multiple_coords 没有要追加的列表，这很容易解决：
def iterate_multiple_coords(the_coordinates):
poly_list = []
for i in the_coordinates:
centre_node = ox.get_nearest_node(mv, (i[0], i[1]))
print("starting" + str(i)) # to check
# add an edge attribute for time in minutes required to traverse each edge
for u, v, k, data in mv_projected.edges(data=True, keys=True):
data['time'] = data['length'] / metres_per_minute
# make the polygons
isochrone_polys_iter = make_iso_polys(mv_projected,
centre_node,
edge_buff=25,
node_buff=0,
infill=True)
print("done " + str([i])) # to check
poly_list.append(isochrone_polys_iter)
print("appended " + str([i])) # to check
return(poly_list)
我尝试使用更多输出进行测试以确定多边形不同：
#list of shapely objects
test = iterate_multiple_coords(multiple_coords)
for i, poly in enumerate(test):
print(i)
print(poly[0].bounds)
print(poly[0].area)
print(poly[1].bounds)
print(poly[1].area)
这个returns对我来说
0
(315719.9722479802, -4183576.0970487385, 317146.7585685815, -4182104.248355794)
1064783.069852857
(316092.45915179665, -4183138.881268308, 316857.3685328224, -4182352.8318315353)
207488.55915115002
1
(311160.15906794026, -4182601.4787744572, 312318.75050440413, -4181146.474157421)
844021.6754682651
(311491.4241338904, -4182296.4498064136, 312171.21314883756, -4181535.6374544636)
181959.15194429446
2
(313349.77854383545, -4179191.5691777603, 314706.9086066517, -4177874.3106440073)
697618.2735243046
(313611.9777962584, -4178837.4315966303, 314316.9596420839, -4178365.0333478907)
105808.08447317046
3
(316506.3163716192, -4182533.536447418, 317712.9680439883, -4181044.336753285)
1042931.7802330595
(316764.0345564607, -4182162.9997046595, 317463.6017386513, -4181398.2886200016)
276870.23606513516
4
(317045.2449636515, -4185110.519037448, 318554.4721278832, -4183677.93438998)
1170827.5838636972
(317408.8052150706, -4184702.3494480574, 318143.3573653238, -4184063.5647333027)
253939.04383932063