Graph-tool简介 - wiki

graph-tool is a Python module for manipulation and statistical analysis of graphs[disambiguation needed] (a.k.a. networks).

graph-tool是一个操作和统计分析图表的Python模块。

The core data structures and algorithms of graph-tool are implemented in C++, making extensive use of metaprogramming, based heavily on the Boost Graph Library.

graph-tool核心的数据结构和算法是用c++实现的,其大量使用元编程,依赖于Boost Graph库。

This type of approach can confer a level of performance which is comparable (both in memory usage and computation time) to that of a pure C++ library, which can be several orders of magnitude better than pure Python.[1]

这种方法会带来一定程度的性能优势，甚至能与纯c++库相匹敌(在内存使用和计算时间上),这可以比单纯使用Python好几个数量级。

Furthermore, many algorithms are implemented in parallel using OpenMP, which provides increased performance on multi-core architectures.

此外,许多算法由并行使用OpenMP实现,这使得其在多核体系结构机器上的性能有显著提升。

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内容

1. 特征
2. 适用性
3. 参考文献
4. 外部链接

1.特征

Creation and manipulation of directed or undirected graphs.

• 直接或间接地创建和操纵图表。

Association of arbitrary information to the vertices, edges or even the graph itself, by means of property maps.

• 通过属性映射，将任意的信息与顶点、边甚至是图本身相关联起来。

Filter vertices and/or edges "on the fly", such that they appear to have been removed.

• “动态”地过滤顶点和/或边,这样它们看起来似乎已经被移除。

Support for dot, Graph Modelling Language and GraphML formats.

• 支持点,图形建模语言和GraphML格式。

Convenient and powerful graph drawing based on cairo or Graphviz.

• 便捷和强大的图形绘制能力（基于cairo和Graphviz）。

Support for typical statistical measurements: degree/property histogram, combined degree/property histogram, vertex-vertex correlations, assortativity, average vertex-vertex shortest path, etc.

• 支持典型的统计指标:degree/property直方图,combined degree/property直方图,vertex-vertex相关性,assortativity vertex-vertex平均最短路径等。

Support for several graph-theoretical algorithms: such as graph isomorphism, subgraph isomormism, minimum spanning tree, connected components, dominator tree, maximum flow, etc.

• 支持几个图形理论算法:例如，图同构，子图同构，最小生成树，连接组件，支配树，最大流法。

Support for several centrality measures.

• 支持多种中心性。

Support for clustering coefficients, as well as network motif statistics and community structure detection.

• 支持集群系数,以及网络motif统计和群体结构检测。

Generation of random graphs, with arbitrary degree distribution and correlations.

• 具有任意分布度和相关性的随机图的生成,。

Support for well-established network models: Price, Barabási-Albert, Geometric Networks, Multidimensional lattice graph, etc.

• 支持已经建立的网络模型：如，Price、Barabasi-Albert、几何网络多维网格图等。

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2.适用性

Graph-tool can be used to work with very large graphs in a variety of contexts, including
Graph-tool可以用来处理各种情况下非常大的图,包括

simulation of cellular tissue
模拟细胞组织
data mining
数据挖掘
analysis of social networks
社交网络分析
analysis of P2P systems,[7]
P2P系统分析
large-scale modeling of agent-based systems,[8]
大规模的基于主体系统的建模
study of academic Genealogy trees,[9]
研究学术家谱树
theoretical assessment
理论评估
and modeling of network clustering,[10]
网络聚类和建模
large-scale call graph analysis,[11][12]
大规模的调用图分析
and analysis of the brain's Connectome.[13]
分析大脑的连接体

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3.参考文献

参见原链接

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4.外部链接

Graph-tool官网

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来源网址：Graph-tool - From Wikipedia, the free encyclopedia