目录
一、官网样例
二、准备工作
1.样例代码下载
2.包安装+环境配置
三、经典样例展示
1.样例 Read and write graphs
2.样例 Edge Colormap
3.样例 Circular Tree
4.样例 Random Geometric Graph
5.样例 Atlas
6.样例 画3D图
一、官网样例
用python做关联图谱（也称关联图、关联网络图、关系图等，关注的是关联关系；而用于搭建知识体系时，则被称做知识图谱），有时候我会选择用networkx来实现，因此有了这篇学习笔记。
在学习python某个包的时候，建议去官网跑一遍样例，如果项目比较急，可以先找到所需的目标样例，针对性的深入学习这个案例中的代码写法和语法逻辑等。
networkx2.5的官网案例链接为：Gallery — NetworkX 2.8.5 documentation
中文版的官网链接为：绘图示例 — NetworkX 2.8 文档
链接里不叫 Examples，而叫 Gallery，所以有的同学不一定能马上找到，点开链接后如下图：
二、准备工作
1.样例代码下载
本人已经将官网上几十个样例代码都放在一个jupyter文件“networkx官网学习笔记.ipynb”中，均已跑通，并附带所需文件。跑出的结果图可能会和官网或我的jupyter中的不一样，属于正常情况，因为是随机的。
下载链接为：https://download.csdn/download/weixin_42575233/20330671
2.包安装+环境配置
A、python安装3.8，即安装 Anaconda3-2020.02-Windows-x86_64.exe，大家可以从我给的链接直接下载，链接为：Anaconda3-2020.02-Windows-x86_64.exe.zip-Python文档类资源-CSDN下载
，也可以到官网上找到这个版本下载并安装，最新版本的安装包能跑通大部分代码，但不敢保证全部都OK。
B、安装networkx包，用pip install networkx即可，网上也有很多相关文章，在此不做赘述，若安装还是有问题，请留言咨询我。
C、安装Graphviz，下载链接:graphviz-2.38.msi.zip_graphviz-2.38.msi-Python文档类资源-CSDN下载，安装方法详见“networkx官网学习笔记.ipynb”，其环境变量配置方法如下
a、找到安装路径，如：C:\Program Files (x86)\Graphviz2.38\bin
b、右键点击“此电脑”选择“属性”，如下图：
c、搜索“高级系统设置”，选择“环境变量”：
d、将bin文件夹对应的路径添加到 Path环境变量中，即双击下图中的Path，在跳出的窗口点“新建”，输入：“C:\Program Files (x86)\Graphviz2.38\bin”，然后点“确定”，完成安装。
D、安装pygraphviz
我这边提供python3.8版本的whl文件，下载链接为：pygraphviz-1.6-cp38-cp38-win_amd64.whl-Python文档类资源-CSDN下载
，也可以在网页http://www.lfd.uci.edu/~gohlke/pythonlibs/#pygraphviz 中找到pygraphviz对应版本的.whl文件下载。
打开Anaconda下的prompt，在其中输入“cd 路径” 切换到下载的.whl文件所在路径的文件夹目录，在prompt再输入命令：pip install pygraphviz-1.6-cp38-cp38-win_amd64.whl，开始安装。如果显示successfully，就代表已经安装好啦。
E、画3D图涉及的4个包：PyQt6、mayavi、traits 和 VTK
一定要按照以下方式逐个安装
第一组，PyQt6直接在prompt输入 pip install PyQt6，进行网络安装即可。
第二组，其余3个，则在我给的下载链接：python3.8画3D图必备whl.zip-Python文档类资源-CSDN下载
下载“python3.8画3D图必备whl.zip”，解压后有3个whl，放入你指定的某个文件夹下面，在prompt中定位到该文件夹的路径，然后逐个输入以下代码进行安装（若显示 Successfully installed，但有红字 ERROR，可忽略报错，因为仍能正常运行代码）：
pip install mayavi-4.7.2-cp38-cp38-win_amd64.whl
pip install traits-6.1.1-cp38-cp38-win_amd64.whl
pip install VTK-9.0.1-cp38-cp38-win_amd64.whl
三、经典样例展示
1.样例 Read and write graphs
代码如下：
# python3.7环境下运行此段代码，第一次跑会不出图，再次运行即可出图
# Read and write graphs
import matplotlib.pyplot as plt
import networkx as nx
G = nx.grid_2d_graph(5, 5) # 5x5 grid
# print the adjacency list
for line in nx.generate_adjlist(G):
print(line)
# write edgelist to grid.edgelist
nx.write_edgelist(G, path="grid.edgelist", delimiter=":")
# read edgelist from grid.edgelist
H = nx.read_edgelist(path="grid.edgelist", delimiter=":")
nx.draw(H)
plt.show()2.样例 Edge Colormap
代码如下：
#%% Edge Colormap
import matplotlib.pyplot as plt
import networkx as nx
num = 17
G = nx.star_graph(num)
pos = nx.spring_layout(G)
colors = range(num)
nx.draw(G, pos, node_color='#A0CBE2', edge_color=colors,
width=4, edge_cmap=plt.cm.Blues, with_labels=True)
plt.show()3.样例 Circular Tree
代码如下：
# Circular Tree
import matplotlib.pyplot as plt
import networkx as nx
try:
import pygraphviz
from networkx.drawing.nx_agraph import graphviz_layout
except ImportError:
try:
import pydot
from networkx.drawing.nx_pydot import graphviz_layout
except ImportError:
raise ImportError("This example needs Graphviz and either "
"PyGraphviz or pydot")
G = nx.balanced_tree(3, 5)
pos = graphviz_layout(G, prog='twopi', args='')
plt.figure(figsize=(8, 8))
nx.draw(G, pos, node_size=20, alpha=0.5, node_color="blue", with_labels=False)
plt.axis('equal')
plt.show()4.样例 Random Geometric Graph
代码如下：
# Random Geometric Graph
import matplotlib.pyplot as plt
import networkx as nx
G = nx.random_geometric_graph(200, 0.125)
# position is stored as node attribute data for random_geometric_graph
pos = nx.get_node_attributes(G, 'pos')
# find node near center (0.5,0.5)
dmin = 1
ncenter = 0
for n in pos:
x, y = pos[n]
d = (x - 0.5)**2 + (y - 0.5)**2
if d < dmin:
ncenter = n
dmin = d
# color by path length from node near center
p = dict(nx.single_source_shortest_path_length(G, ncenter))
plt.figure(figsize=(8, 8))
nx.draw_networkx_edges(G, pos, nodelist=[ncenter], alpha=0.4)
nx.draw_networkx_nodes(G, pos, nodelist=list(p.keys()),
node_size=80,
node_color=list(p.values()),
cmap=plt.cm.Reds_r)
plt.xlim(-0.05, 1.05)
plt.ylim(-0.05, 1.05)
plt.axis('off')
plt.show()5.样例 Atlas
代码如下：
#Atlas
import random
try:
import pygraphviz
from networkx.drawing.nx_agraph import graphviz_layout
except ImportError:
try:
import pydot
from networkx.drawing.nx_pydot import graphviz_layout
except ImportError:
raise ImportError("This example needs Graphviz and either "
"PyGraphviz or pydot.")
import matplotlib.pyplot as plt
import networkx as nx
from networkx.algorithms.isomorphism.isomorph import graph_could_be_isomorphic as isomorphic
from networkx.generators.atlas import graph_atlas_g
def atlas6():
""" Return the atlas of all connected graphs of 6 nodes or less.
Attempt to check for isomorphisms and remove.
"""
Atlas = graph_atlas_g()[0:208] # 208
# remove isolated nodes, only connected graphs are left
U = nx.Graph() # graph for union of all graphs in atlas
for G in Atlas:
zerodegree = [n for n in G if G.degree(n) == 0]
for n in zerodegree:
G.remove_node(n)
U = nx.disjoint_union(U, G)
# iterator of graphs of all connected components
C = (U.subgraph(c) for c in nx.connected_components(U))
UU = nx.Graph()
# do quick isomorphic-like check, not a true isomorphism checker
nlist = [] # list of nonisomorphic graphs
for G in C:
# check against all nonisomorphic graphs so far
if not iso(G, nlist):
nlist.append(G)
UU = nx.disjoint_union(UU, G) # union the nonisomorphic graphs
return UU
def iso(G1, glist):
"""Quick and dirty nonisomorphism checker used to check isomorphisms."""
for G2 in glist:
if isomorphic(G1, G2):
return True
return False
if __name__ == '__main__':
G = atlas6()
print("graph has %d nodes with %d edges"
% (nx.number_of_nodes(G), nx.number_of_edges(G)))
print(nx.number_connected_components(G), "connected components")
plt.figure(1, figsize=(8, 8))
# layout graphs with positions using graphviz neato
pos = graphviz_layout(G, prog="neato")
# color nodes the same in each connected subgraph
C = (G.subgraph(c) for c in nx.connected_components(G))
for g in C:
c = [random.random()] * nx.number_of_nodes(g) # random color...
nx.draw(g,
pos,
node_size=40,
node_color=c,
vmin=0.0,
vmax=1.0,
with_labels=False
)
plt.show()6.样例 画3D图
代码如下（输出png图片）：
# Mayavi: needs mayavi2
# run with ipython -wthread
%matplotlib inline
import networkx as nx
import numpy as np
from mayavi import mlab
mlab.options.offscreen = True
# some graphs to try
# H=nx.krackhardt_kite_graph()
# H=nx.Graph();H.add_edge('a','b');H.add_edge('a','c');H.add_edge('a','d')
# H=nx.grid_2d_graph(4,5)
H = nx.cycle_graph(20)
# reorder nodes from 0,len(G)-1
G = nx.convert_node_labels_to_integers(H)
# 3d spring layout
pos = nx.spring_layout(G, dim=3)
# numpy array of x,y,z positions in sorted node order
xyz = np.array([pos[v] for v in sorted(G)])
# scalar colors
scalars = np.array(list(G.nodes())) + 5
mlab.figure(1, bgcolor=(0, 0, 0))
mlab.clf()
pts = mlab.points3d(xyz[:, 0], xyz[:, 1], xyz[:, 2],
scalars,
scale_factor=0.1,
scale_mode='none',
colormap='Blues',
resolution=20)
pts.mlab_source.dataset.lines = np.array(list(G.edges()))
tube = mlab.pipeline.tube(pts, tube_radius=0.01)
mlab.pipeline.surface(tube, color=(0.8, 0.8, 0.8))
mlab.savefig('mayavi2_spring.png')
mlab.show() # interactive window完整样例，请大家在我的学习笔记里面，逐个运行看看效果吧！
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