绘制包含多个组件的图形时节点大小不正确 [英] Node sizes not correct when drawing a graph with many components

问题描述

我有一个包含许多组件的图表，我想对其进行可视化.作为一个特殊的特征，巨型组件中节点的节点点将随着它们的特征向量中心性而缩放.所有其他节点的大小相同.

I've got a graph with many components which I would like to visualize. As a special feature, the node dots of the nodes in the giant component shall scale with their eigenvector centrality. All the other nodes have same size.

我使用以下脚本:

import networkx as nx
import pylab as py
import matplotlib.pyplot as plt

H = nx.read_gexf(input_file)
print nx.info(H)
#Name: 
#Type: Graph
#Number of nodes: 719
#Number of edges: 620
#Average degree:   1.7246

# Set draw() parameters
node_sizes = dict.fromkeys(H.nodes(), 0.005)
# Make node size of giant component nodes proportional to their eigenvector
eigenvector = nx.eigenvector_centrality_numpy(G)
for node, value in eigenvector.iteritems():
    node_sizes[node] = round(value, 4)
node_sizes = [v*2000 for v in node_sizes.values()] # rescale
node_positions = nx.pygraphviz_layout(H, prog="neato")

# Draw graph with different color for each connected subgraph
plt.figure(3, figsize=(90,90))
nx.draw(H, font_size=10, pos=node_positions, node_size=node_sizes, vmin=0.0, vmax=1.0, with_labels=True)
plt.show()

一切都非常正确，因为我检查了不同的输出.但是，我收到一个输出，其中来自巨型组件以外的组件的某些节点是缩放的.此外，巨型组件中的节点没有正确缩放.

Everything is quite correct, as I checked in distinct outputs. However, I receive an output where some nodes from components other than the giant component are scale. Moreover, the nodes in the giant component are not correctly scaled.

此快照显示了巨型组件和带有缩放节点的非组件:

This snapshot shows the giant component and an off-component with a scaled node:

但是，如果我只使用字典 eigenvector 作为节点大小打印巨型组件 G，我会得到以下 - 正确 - 输出 (:

However, if I only print the giant component G using the dictionary eigenvector for the node size, I get the following - correct - output (:

我也做了一些故障排除.例如，字典/列表 node_sizes 都是正确的.有趣的是，使用随机图 H = nx.fast_gnp_random_graph(300, 0.005, seed=5) 会返回正确的结果.因此，我完全不知道我的 H 出了什么问题.

I did some troubleshooting, too. For example, the dictionary/list node_sizes is all correct. Interestingly, using a random graph H = nx.fast_gnp_random_graph(300, 0.005, seed=5) returns correct results. Therefore I have absolutely no idea what's wrong with my H.

推荐答案

您会注意到 node_sizes 是一个列表.您尚未向 draw 命令发送节点列表.它将从网络中的节点动态生成它们.当这两个列表的顺序不同时，就会出现问题.我认为拥有多个组件不是问题，而是您的网络越大，它们的排列顺序就越有可能不同.

You'll notice that node_sizes is a list. You haven't sent the draw command a list of nodes. It's going to generate them on the fly from the nodes in the network. The problem occurs when these two lists end up being in different orders. I don't think it's an issue with having multiple components, but rather the larger your network is the more likely it is that they aren't put into the same order.

所以而不是

node_sizes = [v*2000 for v in node_sizes.values()]

使用

nodelist, node_sizes = zip(*node_sizes.items())

这里 nodelist 将获取 node_sizes.items 的每个条目中第一个数字的列表，node_sizes 将获取每个条目中第二个数字的列表.

here nodelist will get the list of the first numbers in each entry of node_sizes.items and node_sizes will get the list of the second numbers in each entry.

然后在绘图命令中给它节点列表

Then in the plotting command give it the nodelist

nx.draw(H, font_size=10, pos=node_positions, node_size=node_sizes, vmin=0.0, vmax=1.0, with_labels=True, nodelist=nodelist)

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