draw(G, pos, 40 with_labels=False, 41 node_size=10 42 ) 43 # identify largest connected component 44 Gcc = sorted(nx.connected_component_subgraphs(G), key=len, reverse=True) 45 G0 = Gcc[0] 46 nx.draw_networkx_edges(G0, pos, 47 with_labels=False, 48 edge_color='r', 49 width=...
图标Graph 本文参考: https://networkx.github.io/documentation/stable/auto_examples/index.html 1. 基础Basic 读写图 Read and write graphs 属性Properties ## 读写图 Read and write graphs# Author: Aric Hagberg (hagberg@lanl.gov)# Copyright (C) 2004-2019 by# Aric Hagberg <hagberg@lanl.gov># Da...
largest_cc = max(nx.connected_components(G), key=len)#获取最大的连通子图参考资料【1】http://networkx.github.io/documentation/networkx-1.9/reference/api_1.9.html#miscellaneous-changes【2】http://stackoverflow.com/questions/26105764/how-do-i-get-the-giant-component-of-a-networkx-graph/26105849#...
G = nx.generators.barabasi_albert_graph(n, m) # find node with largest degree node_and_degree = G.degree() (largest_hub, degree) = sorted(node_and_degree, key=itemgetter(1))[-1] # Create ego graph of main hub hub_ego = nx.ego_graph(G, largest_hub) # Draw graph pos = nx.s...
nx_load_shp = nx.read_shp("../geodata/shp/e01_network_lines_3857.shp")#A graph is not always connected, so we take the largest connected subgraph#by using the connected_component_subgraphs function.#获取连接子图nx_list_subgraph =list(nx.connected_component_subgraphs(nx_load_shp.to_...
例如在读取football数据时，其labels都是节点的英文名称，这样在处理图数据时不是很方便，往往报错，我们...
要计算网络中的最大组件,我们可以使用nx.connected_components()函数。这将返回一个包含网络中所有连通分量集合的生成器。我们可以使用以下代码来计算最大组件: components=list(nx.connected_components(G))largest_component=max(components,key=len) 可视化最大组件 ...
connected_component_subgraphs(G), key=len) # Option 2 for component in list(nx.connected_components(G)): if len(component) < 16451: # Size of the largest component for node in component: G.remove_node(node) 复制Copyright © 2020 - 2025 版权所有 蜀ICP备20006366号-1 Made with ...
hspace=0.01) for p in pvals: G = nx.binomial_graph(n, p) pos = layout(G) region += 1 plt.subplot(region) plt.title(f"p = {p:.3f}") nx.draw(G, pos, with_labels=False, node_size=10) # identify largest connected component Gcc = sorted(nx.connected_components(G), key=len,...
(list) for n, p in zip(list(range(len(G))), membership): partition[p].append(n) return list(partition.values()) G = nx.read_edgelist("hartford_drug.edgelist") # Extract largest connected component into graph H H = G.subgraph(next(nx.connected_components(G))) # Makes life easier ...