神经网络图形绘制

在python机器学习中会遇到各种各样的神经网络图形,以下为例子:

"""======================

Betweenness Centrality

======================

Betweenness centrality measures of positive gene functional associations

using WormNet v.3-GS.

Data from: https://www.inetbio.org/wormnet/downloadnetwork.php

"""

from random import sample

import networkx as nx

import matplotlib.pyplot as plt

Gold standard data of positive gene functional associations

from https://www.inetbio.org/wormnet/downloadnetwork.php

G = nx.read_edgelist("D:/OneDrive - stu.fynu.edu.cn/Gephi/WormNet.v3.benchmark.txt")

remove randomly selected nodes (to make example fast)

num_to_remove = int(len(G) / 1.5)

nodes = sample(list(G.nodes), num_to_remove)

G.remove_nodes_from(nodes)

remove low-degree nodes

low_degree = [n for n, d in G.degree() if d < 10]

G.remove_nodes_from(low_degree)

largest connected component

components = nx.connected_components(G)

largest_component = max(components, key=len)

H = G.subgraph(largest_component)

compute centrality

centrality = nx.betweenness_centrality(H, k=10, endpoints=True)

compute community structure

lpc = nx.community.label_propagation_communities(H)

community_index = {n: i for i, com in enumerate(lpc) for n in com}

draw graph

fig, ax = plt.subplots(figsize=(20, 15))

pos = nx.spring_layout(H, k=0.15, seed=4572321)

node_color = [community_index[n] for n in H]

node_size = [v * 20000 for v in centrality.values()]

nx.draw_networkx(

H,

pos=pos,

with_labels=False,

node_color=node_color,

node_size=node_size,

edge_color="gainsboro",

alpha=0.4,

)

Title/legend

font = {"color": "k", "fontweight": "bold", "fontsize": 20}

ax.set_title("Gene functional association network (C. elegans)", font)

Change font color for legend

font["color"] = "r"

ax.text(

0.80,

0.10,

"",

#"node color = community structure",

horizontalalignment="center",

transform=ax.transAxes,

fontdict=font,

)

ax.text(

0.80,

0.06,

"",

#"node size = betweenness centrality",

horizontalalignment="center",

transform=ax.transAxes,

fontdict=font,

)

Resize figure for label readability

ax.margins(0.1, 0.05)

fig.tight_layout()

plt.axis("off")

plt.savefig("D:/OneDrive - stu.fynu.edu.cn/Gephi/WormNet.v3.benchmark.png")

plt.show()

这样绘制出图形如下:

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