按地点对 osmnx 地图进行着色（使用 graph_from_place() 方法）

Question

我们绘制了2个位置：

# Get data
import osmnx as ox
place = ["Broughton Hackett", "Crowle"]
G = ox.graph_from_place(place, retain_all=True, simplify = True, network_type='all')

# Prepare data
u = []
v = []
key = []
data = []
for uu, vv, kkey, ddata in G.edges(keys=True, data=True): # added ww
    u.append(uu)
    v.append(vv)
    key.append(kkey)
    data.append(ddata)

# Define colors according to length of streets
roadCols = []

for item in data:    
    if "length" in item.keys():
        if item["length"] <= 200:
            color = "#FFFFF0"             
        elif item["length"] > 200 and item["length"] <= 1000:
            color = "#6a0dad"  
        else:
            color = "#00FFFF"
    else:
        color = "#FFFFFF"         
    roadCols.append(color)

#Plot 
bgcolor = "#1e1e1e"
fig, ax = ox.plot_graph(G, node_size=0, 
                        dpi = 100,bgcolor = bgcolor,
                        save = False, edge_color=roadCols,
                        edge_linewidth=1, edge_alpha=1)
fig.tight_layout(pad=0)
fig.savefig("stack.jpg", dpi=100, bbox_inches='tight', format="jpg", 
            facecolor=fig.get_facecolor(), transparent=False)

正如我们在下面的输出中看到的那样，街道已根据其长度进行着色。

我的问题：我们如何为 place 而不是长度彩色街道吗？因此，第一村的所有街道都采用一种颜色，而另一村的所有街道都采用另一种颜色？

与长度相反，该位置不包含在data对象中，我不知道如何检索它。

这是一个模拟的例子，我有意选择了小村庄。实际上，我想通过一系列整个城市进行着色。

Answer 1

• 能够根据地点对边缘进行着色的核心是知道该地点
• 已使用获取每个地点的 osmnx* 图表并为其分配地点的方法
• ，然后使用 geopandas 就很简单/ folium 与颜色边缘的集成
• 也显示了似乎是首选的方式 ma​​tplotlib

Matplotlib

# Get data
import osmnx as ox
import pandas as pd
from matplotlib.colors import ListedColormap
import matplotlib.pyplot as plt

plt.style.use('dark_background')

place = ["Broughton Hackett", "Crowle"]
gdf_nodes = gdf_edges = None
for place in place:
    G = ox.graph_from_place(place, retain_all=True, simplify = True, network_type='all')
    n_, e_ = ox.graph_to_gdfs(G)
    n_["place"] = place
    e_["place"] = place
    if gdf_nodes is None:
        gdf_nodes = n_
        gdf_edges = e_
    else:
        gdf_nodes = pd.concat([gdf_nodes, n_])
        gdf_edges = pd.concat([gdf_edges, e_])

# it's a bit imperfect way to map a value to a color
colors = {'Broughton Hackett':'red', 'Crowle':'blue'}
gdf_edges.plot(column="place", cmap=ListedColormap([colors[k] for k in sorted(colors.keys())]))

大叶

# Get data
import osmnx as ox
import pandas as pd
place = ["Broughton Hackett", "Crowle"]
gdf_nodes = gdf_edges = None
for place in place:
    G = ox.graph_from_place(place, retain_all=True, simplify = True, network_type='all')
    n_, e_ = ox.graph_to_gdfs(G)
    n_["place"] = place
    e_["place"] = place
    if gdf_nodes is None:
        gdf_nodes = n_
        gdf_edges = e_
    else:
        gdf_nodes = pd.concat([gdf_nodes, n_])
        gdf_edges = pd.concat([gdf_edges, e_])

gdf_edges.explore(column="place", height=300, width=500)