This article may rely excessively on sources
too closely associated with the subject, potentially preventing the article from being
verifiable and
neutral. (January 2021) |
![]() | |
Developer(s) | Tiago P. Peixoto |
---|---|
Stable release | 2.45
/ 22 May 2022 |
Repository | |
Written in | Python, C++ |
Operating system | OS X, Linux |
Type | Software library |
License | LGPL |
Website |
graph-tool |
graph-tool is a Python module for manipulation and statistical analysis of graphs (AKA networks). 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. [1] Many algorithms are implemented in parallel using OpenMP, which provides increased performance on multi-core architectures.
Graph-tool can be used to work with very large graphs [ clarification needed] in a variety of contexts, including simulation of cellular tissue, [2] data mining, [3] [4] analysis of social networks, [5] [6] analysis of P2P systems, [7] large-scale modeling of agent-based systems, [8] study of academic Genealogy trees, [9] theoretical assessment and modeling of network clustering, [10] large-scale call graph analysis, [11] and analysis of the brain's Connectome. [12]
This article may rely excessively on sources
too closely associated with the subject, potentially preventing the article from being
verifiable and
neutral. (January 2021) |
![]() | |
Developer(s) | Tiago P. Peixoto |
---|---|
Stable release | 2.45
/ 22 May 2022 |
Repository | |
Written in | Python, C++ |
Operating system | OS X, Linux |
Type | Software library |
License | LGPL |
Website |
graph-tool |
graph-tool is a Python module for manipulation and statistical analysis of graphs (AKA networks). 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. [1] Many algorithms are implemented in parallel using OpenMP, which provides increased performance on multi-core architectures.
Graph-tool can be used to work with very large graphs [ clarification needed] in a variety of contexts, including simulation of cellular tissue, [2] data mining, [3] [4] analysis of social networks, [5] [6] analysis of P2P systems, [7] large-scale modeling of agent-based systems, [8] study of academic Genealogy trees, [9] theoretical assessment and modeling of network clustering, [10] large-scale call graph analysis, [11] and analysis of the brain's Connectome. [12]