Python 3.x 根据节点之间的欧几里德距离指定边权重

我正在创建一个包含50个随机创建的节点的完整图形。每个节点定义为笛卡尔坐标，如下所示：

n = 50
V = []
V=range(n)

random.seed()

pos = {i:(random.randint(0,500),random.randint(0,500)) for i in V}

我需要指定每个节点之间的欧几里德距离，因为边权重对应于这对节点

我已经定义了两个节点之间的欧几里德距离，如下所示：

points = []
positions = []
for i in pos:
    points.append(pos[i])
    positions.append(i)
    positions.append(pos[i])

def distance(points, i, j):
    dx = points[i][0] - points[j][0]
    dy = points[i][1] - points[j][1]
    return math.sqrt(dx*dx + dy*dy)

for u in V:
    for v in V:
        weights = distance(points, u,v)

G = nx.complete_graph(n)
for e in G.edges():
   weights[e] = distance(points, e[0],e[1])

我尝试将欧几里德距离指定为它们的权重，如下所示：

points = []
positions = []
for i in pos:
    points.append(pos[i])
    positions.append(i)
    positions.append(pos[i])

def distance(points, i, j):
    dx = points[i][0] - points[j][0]
    dy = points[i][1] - points[j][1]
    return math.sqrt(dx*dx + dy*dy)

for u in V:
    for v in V:
        weights = distance(points, u,v)

G = nx.complete_graph(n)
for e in G.edges():
   weights[e] = distance(points, e[0],e[1])

但这将返回以下错误

    weights[e] = distance(points, e[0],e[1])

TypeError: 'float' object does not support item assignment

---

有人能给我一个建议吗

你的问题是

for u in V:
    for v in V:
        weights = distance(points, u,v)

权重

是一个浮点值（比较的最后一对的距离）

现在你知道了

for e in G.edges():
    weights[e] = distance(points, e[0],e[1])

您将浮点

权重
的
e
th项指定为某物。不允许

我想你想要的是

for u,v in G.edges():
    G[u][v]['distance'] = distance(points, u, v)

请注意，与其定义
点
，不如将节点设为笛卡尔坐标的元组。参见
除了Joel提到的内容之外，下面是有效的代码

import random
import networkx as nx
import math
import itertools    
import matplotlib.pyplot as plt
n = 50
V = []
V=range(n)

random.seed()

pos = {i:(random.randint(0,500),random.randint(0,500)) for i in V}
points = []
positions = []
for i in pos:
    points.append(pos[i])
    positions.append(i)
    positions.append(pos[i])

def distance(points, i, j):
    dx = points[i][0] - points[j][0]
    dy = points[i][1] - points[j][1]
    return math.sqrt(dx*dx + dy*dy)

G=nx.empty_graph(n)

for u in V:
    for v in V:
        wt = distance(points, u,v)
        G.add_edge(u,v,weight = wt)

nx.draw(G,pos)
edges,weights = zip(*nx.get_edge_attributes(G,'weight').items())
nx.draw(G, pos, node_color='k', edgelist=edges, edge_color=weights, width=1, edge_cmap=plt.cm.Reds)