Question

我创建了一个包含50个随机创建节点的完整图表。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}

我需要在每个节点之间分配欧几里德距离，因为边缘权重对应于那对节点。

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)

我尝试将欧几里德距离指定为其权重如下：

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])

但是这会返回以下错误。

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

TypeError: 'float' object does not support item assignment

有人可以建议我这样做吗？

Answer 1

你遇到的问题是

之后

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

weights是一个浮点数（比较最后一对的距离）。

现在你做

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

您正在指定浮动e的{{1}}项。不允许。

我认为你想要的是

weights

作为一个注释，我不是定义for u,v in G.edges(): G[u][v]['distance'] = distance(points, u, v)，而是让节点成为笛卡尔坐标的元组。见Relabeling Nodes of a graph in networkx

Answer 2

除了Joel提到的内容之外，以下是可行的代码。

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)

Edges colored by edgeweights

从节点之间的欧几里德距离分配边权重

2 个答案: