相关疑难解决方法(0)

我正在使用Python来模拟在有向图上发生的过程.我想制作一个这个过程的动画.

我遇到的问题是大多数Python图形可视化库将成对的有向边组合成一个边.例如,NetworkX在显示下图时只绘制两条边,而我想分别显示四条边的每一条:

import networkx as nx
import matplotlib.pyplot as plt 

G = nx.MultiDiGraph()

G.add_edges_from([
    (1, 2),
    (2, 3),
    (3, 2),
    (2, 1),
])

plt.figure(figsize=(8,8))
nx.draw(G)

我想显示这样的东西,每个平行边缘分开绘制:

R中的igraph中的R倒数边缘的问题似乎处理相同的问题,但是解决方案存在于R igraph库,而不是Python.

有没有一种简单的方法可以使用现有的Python图形可视化库生成这种样式的绘图？如果它可以支持多图,那将是一个奖励.

我愿意接受调用外部程序来生成图像的解决方案.我想生成一系列动画帧,因此解决方案必须自动化.

In the class networkx.MultiGraph, an edge is keyed by (u, v, key), for instance, ('n1', 'n2', 'key1'). I would like to draw edge labels (say weight, (u, v, key): 10) for MultiGraph by using the function networkx.draw_networkx_edge_labels.

However, edge labels are keyed by a two-tuple (u, v) in draw_networkx_edge_labels, instead of a 3-tuple (u, v, key), as is the case in MultiGraph. This raises ValueError: too many values to unpack.

PS: …

我想使用networkx（如果您知道更好的框架，我也想采用其他框架）来创建节点位于固定位置的抓图。同时，图形的边缘不应重叠。

我之前的代码如下：

#!/usr/bin/env python3

import networkx as nx
import matplotlib.pyplot as plt

# Graph data
names = ['A', 'B', 'C', 'D', 'E']
positions = [(0, 0), (0, 1), (1, 0), (0.5, 0.5), (1, 1)]
edges = [('A', 'B'), ('A', 'C'), ('A', 'D'), ('A', 'E'), ('D', 'A')]

# Matplotlib figure
plt.figure('My graph problem')

# Create graph
G = nx.MultiDiGraph(format='png', directed=True)

for index, name in enumerate(names):
    G.add_node(name, pos=positions[index])

labels = {}
for edge in edges:
    G.add_edge(edge[0], edge[1])
    labels[(edge[0], edge[1])] = '{} -> …

我目前的networkx图表有以下代码：

import matplotlib.pyplot as plt
import networkx as nx


g = nx.Graph()
# add edges
g.add_edge("a", "b", weight=0.6)
g.add_edge("a", "c", weight=0.2)
g.add_edge("c", "d", weight=0.1)
g.add_edge("c", "e", weight=0.7)
g.add_edge("c", "f", weight=0.9)
g.add_edge("a", "d", weight=0.3)
# group edges by attribute "weight"
elarge = [
    (u, v) for (u, v, d) in g.edges(data=True)
    if d["weight"] > 0.5]
esmall = [
    (u, v) for (u, v, d) in g.edges(data=True)
    if d["weight"] <= 0.5]
# compute the positions of nodes
pos = nx.circular_layout(g) …

我正在尝试使用 python 中的networks.draw() 函数绘制图形。尽管它不是有向图，但我的图的边缘按拓扑排序顺序排列。我想打印看起来像依赖 DAG 的图表以获得更好的可见性。目标是这样的：

我该怎么做？