如何使用路线的距离创建颜色图

I have slightly added to your code. This will help in colouring the nodes based on their topological distance (since you did not pass any specific weight while calculating the shortest path, the shortest path is calculated based on the number of edges needed to be traversed to reach the destination as each edge is assigned a weight of 1).

I start after target_1 = ox.get_nearest_node(G, coord_1)

Obtain the nodes and edges geodataframes from the graph. We need the nodes geodataframe for this purpose.

nodes, edges = ox.graph_to_gdfs(G, nodes=True, edges=True)

We then calculate the shortest path, the shortest path length, and assign the latter to a new column in the nodes geodataframe.

nodes['shortest_route_length_to_target'] = 0
routes = []
route_lengths = []
i = 0
for node in G.nodes:
    try:
        route = nx.shortest_path(G, node, target_1)
        route_length = nx.shortest_path_length(G, node, target_1)
        routes.append(route)
        route_lengths.append(route_length)
        nodes['shortest_route_length_to_target'][node] = route_length
    except nx.exception.NetworkXNoPath:
        continue

Now we define the following functions. You will notice that these functions are the ones already existing in the file plot.py but are slightly modified for this purpose.

import numpy as np
import matplotlib.cm as cm

def get_colors(n, cmap='viridis', start=0., stop=1., alpha=1.,):

    colors = [cm.get_cmap(cmap)(x) for x in np.linspace(start, stop, n)]
    colors = [(r, g, b, alpha) for r, g, b, _ in colors]
    return colors


def get_node_colors_by_attr(G, attr, num_bins=None, cmap='viridis', start=0, stop=1, na_color='none'):

    if num_bins is None:
        num_bins=len(G.nodes())
    bin_labels = range(num_bins)
    # attr_values = pd.Series([data[attr] for node, data in G.nodes(data=True)])
    attr_values = pd.Series(nodes[attr].values)
    cats = pd.qcut(x=attr_values, q=num_bins, labels=bin_labels)
    colors = get_colors(num_bins, cmap, start, stop)
    node_colors = [colors[int(cat)] if pd.notnull(cat) else na_color for cat in cats]
    return node_colors

Now the following lines of code will give you your desired output.

nc = get_node_colors_by_attr(G, attr = 'shortest_route_length_to_target', num_bins=20,)
fig, ax = ox.plot_graph(G, node_color = nc, fig_height=20,)

您可以更改颜色图（cmap）或num_bins希望将route_lengths值离散化到的仓数（）。