networkx | 易学教程

python Networkx绘图4

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参考Link：（9）Python NetworkX库实现复杂网络 https://blog.csdn.net/qq_33638791/article/details/61923788 1.具有社团结构的网络 ( Networks with Community Structure ) 定义：对于一个图G而言，如果其中有一个完全子图（任意两个节点之间均存在边），节点数是k，那么这个完全子图就可称为一个k-clique。进而，如果两个k-clique之间存在k-1个共同的节点，那么就称这两个clique是“相邻”的。彼此相邻的这样一串clique构成最大集合，就可以称为一个社区，且社区是可以重叠的； import networkx as nx import matplotlib . pyplot as plt G = nx . complete_graph ( 5 ) #返回具有N个节点的完整图，节点标签是0~n-1 K5 = nx . convert_node_labels_to_integers ( G , first_label = 2 ) #G为复杂网络图，指定编号节点中的起始偏移量，新的整数标签编号为first_label，...，n-1 + first_label。 G . add_edges_from ( K5 . edges ( ) ) #对地图中添加边 c =

python Networkx绘图5

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参考Link：（10）Python利用igraph绘制复杂网络聚类（社区检测）结果图 https://blog.csdn.net/liuhuan323/article/details/78936781 # Python 2.7 from igraph import * from PIL import Image colors_type = [ "yellow" , "red" , "green" , "coral" , "alice blue" , "cyan" , "pink" , "gray" , "blue" , "green yellow" , "orange" , "light blue" , "hot pink" , "light green" , "gold" ] def PlotNetworks ( net_file , detected_label , real_label = "Unknown Type" ) : ## read files network = Graph . Read_Adjacency ( net_file ) Graph . to_undirected ( network ) f1 = open ( detected_label ) line = f1 . readline ( ) line = line . strip ( ) str

python Networkx绘图2

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参考Link：（3）重点链接： Examples-General-purpose and introductory examples for NetworkX. https://networkx.github.io/documentation/latest/auto_examples/index.html （4）python绘制随机网络图形 https://blog.csdn.net/u012369559/article/details/78289028 （5）python对网络图networkx进行社区检测和彩色绘图 https://blog.csdn.net/qq_19600291/article/details/102543036 （6）文本分析之制作网络关系图 Python https://www.sohu.com/a/136307045_116235 （3）Examples-General-purpose and introductory examples for NetworkX. （4）python绘制随机网络图形 #注：用erdos_renyi_graph(n,p)方法生成一个含有n个节点、以概率p连接的ER随机图，在本程序中以概率0.8连接20个节点中的每一对节点，完成图形。 import networkx as ne #导入建网络模型包，命名ne import

Preventing Overlap of edges and nodes with NetwrokX/Matplotlib

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问题 I am trying to plot numbers of a problem "Collatz Conjecture" which forms a nice network between numbers(node labels). However, in the final plot of the solution using networkx nx.spring_layout(G) I get overlapping edges and nodes: The nx.spring_layout is configured(through trial and error) as: pos=nx.spring_layout(G,k = 0.004, iterations = 500, scale = 0.6) nx.draw(G, labels=labels, pos=pos, font_size = 6, alpha = 0.5, node_size = nodes.values()) plt.show() Is there a particular way to

Networkx - How to get shortest path length between nodes showing node id instead of label

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问题 I'm new to using NetworkX library with Python. Let's say that I import a Pajek-formatted file: import networkx as nx G=nx.read_pajek("pajek_network_file.net") G=nx.Graph(G) The contents of my file are (In Pajek, nodes are called "Vertices"): *Network *Vertices 6 123 Author1 456 Author2 789 Author3 111 Author4 222 Author5 333 Author6 *Edges 123 333 333 789 789 222 222 111 111 456 Now, I want to calculate all the shortest path lengths between the nodes in my network, and I'm using this function

Networkx - How to get shortest path length between nodes showing node id instead of label

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Python NetworkX — set node color automatically based on a list of values

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问题 I generated a graph with networkx import netwokx as nx s = 5 G = nx.grid_graph(dim=[s,s]) nodes = list(G.nodes) edges = list(G.edges) p = [] for i in range(0, s): for j in range(0, s): p.append([i,j]) for i in range(0, len(nodes)): G.node[nodes[i]]['pos'] = p[i] pos = {} for i in range(0, len(nodes)): pos[nodes[i]] = p[i] nx.draw(G, pos) Now I would like to assign a value to each node between 0 and 4 import random val = [] for i in range(0, len(G.nodes()): val.append(randint(0,4)) And I would

How to write a code for link prediction precision assessment in python?

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问题 I am doing a link prediction problem using the adamic_adar index. The dataset is a grid network(edgelist with 1000 links). I randomly selected 80% (800) of the edges from the observed dataset. I need to select the highest 200 predicted links from preds as below and also calculate the precision ratio. I dont know what to do next. How would I do..help! import numpy as np import networkx as nx G = nx.read_edgelist('Grid.txt', create_using=nx.Graph(), nodetype=int) preds = nx.adamic_adar_index(G)

Adding an edge/node with a color attribute

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问题 I a using the networkx package of Python. The documentation says we can do H.add_edge(1,2,color='blue') but the output shows an edge with the default (black) color. When I do H.add_node(12,color='green') I get a new node with same default red color. 回答1: Peter, according to the documentation, to change the color with which nodes/edges are drawn , you have to provide the node_color argument to the drawing function . I.e. from this example, to draw a graph like this (note different colors of

Networkx: Use common function for edge weight calculation

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问题 Suppose I have a function euc_2d(graph, n1, n2) that calculates the euclidean distance between two nodes of the same graph. Each nodes has a given pos=(x,y) which is assigned on graph creation. NetworkX provides a function to get the total weight of all edges of a graph namely graph.size(weight='weight') . The problem with this method is that it assumes that whenever I add an edge I should explicitly assign the appropriate edge weight like graph.add_edge(u,v,weight=?) using a lambda function