python之networkx 绘制函数的图例

所以我有以下功能来绘制我正在处理的问题。它基本上是一个关键节点检测问题或拦截。我有一些值 x，并决定攻击节点 z。基本上我想用事件和非事件节点以及正在处理/攻击的节点为我的图表着色。这是我目前所拥有的。

def draw_solution(g, zsolution, xsolution, T, xmin=0, filename='test.pdf'):

# draw solution 
pos = {n: ndata['coord'] for n,ndata in g.nodes_iter(data=True)} 
ncolour=[] 
for n,ndata in g.nodes_iter(data=True): 
    if ndata['fuel_load'] < xmin: 
        ncolour.append('gold') 
    else: 
        ncolour.append('yellowgreen') 
pp = PdfPages(filename) 
fig = plt.figure(figsize=(11.7,8.3)) 
fig.suptitle('full graph and initial fuel load') 
plt.axis('off') 
nx.draw_networkx(g, pos, font_size=9, node_color=ncolour) 
fig.savefig(pp, format='pdf') 
fig.clf() 
 
for t in range(T): 
    g_copy = g.copy() 
    #node colour 
    ncolour=[] 
    for i in g.nodes_iter(): 
        if zsolution[i,t] > 0.99: 
            ncolour.append('lightcoral') 
            #g_copy.remove_edges_from(g.edges(i)) 
        elif xsolution[i,t] < xmin: 
            ncolour.append('gold') 
            g_copy.remove_edges_from(g.edges(i)) 
        else: 
            ncolour.append('yellowgreen') 
 
    plt.axis('off') 
    fig.suptitle('t={}, before treatment'.format(t)) 
    nx.draw_networkx(g_copy, pos, font_size=9, node_color=ncolour, label=ncolour) 
    fig.savefig(pp, format='pdf') 
    fig.clf() 
 
    g_copy = g.copy() 
    #node colour 
    ncolour=[] 
    for i in g.nodes_iter(): 
        if zsolution[i,t] > 0.99: 
            ncolour.append('lightcoral') 
            g_copy.remove_edges_from(g.edges(i)) 
        elif xsolution[i,t] < xmin: 
            ncolour.append('gold') 
            g_copy.remove_edges_from(g.edges(i)) 
        else: 
            ncolour.append('yellowgreen') 
 
    plt.axis('off') 
    fig.suptitle('t={}, after treatment'.format(t)) 
    nx.draw_networkx(g_copy, pos, font_size=9, node_color=ncolour, label=ncolour) 
    fig.savefig(pp, format='pdf') 
    fig.clf() 
 
pp.close() 
fig.clf()   

出于某种原因我无法正确理解图例？

求助!谢谢!

请您参考如下方法:

这就是你想要的吗？

import networkx as nx 
import matplotlib.pyplot as plt 
 
G = nx.fast_gnp_random_graph(20,0.2) 
 
rednodes = [1,2,4,5] 
bluenodes = [10,12] 
greennodes = [3,6,9] 
yellowgreennodes = [node for node in G.nodes() if 
                    node not in rednodes + greennodes + bluenodes] 
pos = nx.spring_layout(G) 
nx.draw_networkx_nodes(G, pos=pos, nodelist=rednodes, 
                       node_color='red', label='red nodes') 
nx.draw_networkx_nodes(G, pos=pos, nodelist=bluenodes, 
                       node_color='blue', label='blue nodes') 
nx.draw_networkx_nodes(G, pos=pos, nodelist=greennodes, 
                       node_color='green', label='green nodes') 
nx.draw_networkx_nodes(G, pos=pos, nodelist=yellowgreennodes, 
                       node_color='yellowgreen', label='yellowgreen nodes') 
nx.draw_networkx_edges(G, pos=pos) 
plt.legend(scatterpoints = 1) 
plt.show()