communities
Library of community detection algorithms and visualization tools (by shobrook)
traph
A terminal/cmd graph algorithm visualiser (by 1MaxKoval)
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| communities | traph | |
|---|---|---|
| 12 | 1 | |
| 697 | 3 | |
| - | - | |
| 4.0 | 10.0 | |
| 6 months ago | over 1 year ago | |
| Python | Python | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
communities
Posts with mentions or reviews of communities.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-02-22.
-
I made a graph neural network specifically for graphs with community structure
I made a tool for plotting graphs with community structure. You can check it out here.
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[OC] Algorithmically organizing a social network into cliques
A few people are asking what this is a visualization of. OP's graphs look very similar to an example of the Louvain Method shown in the library's documentation. The Louvain Method is a community detection algorithm used on network graphs. It works by iteratively optimizing modularity of the graph. Modularity is a measure of the density of the number of edges (lines between nodes) that fall within a given group/cluster compared to what would be expected from a random distribution of edges throughout the graph.
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Algorithmically organizing a social network into cliques
I made this visualization with: https://github.com/shobrook/communities
- I made Communities: a library of clustering algorithms for network graphs (link in comments)
- [P] I made Communities: a library of clustering algorithms for network graphs (link in comments)
- I made a library for organizing social networks into cliques (link in comments)
- [P] I made communities: a library for detecting and visualizing clusters in network graphs (link in comments)
- I made 'communities' – a library of clustering algorithms for graphs
- I made 'communities' – a library for detecting communities in graphs, built on numpy
- [Project] I made a lightweight Python library for graph clustering
traph
Posts with mentions or reviews of traph.
We have used some of these posts to build our list of alternatives
and similar projects.
What are some alternatives?
When comparing communities and traph you can also consider the following projects:
graphtage - A semantic diff utility and library for tree-like files such as JSON, JSON5, XML, HTML, YAML, and CSV.
pytextrank - Python implementation of TextRank algorithms ("textgraphs") for phrase extraction
pygraphblas - GraphBLAS for Python
leidenalg - Implementation of the Leiden algorithm for various quality functions to be used with igraph in Python.
NetworkX - Network Analysis in Python
libmaths - A Python library created to assist programmers with complex mathematical functions