This is the main repository for the Graph-Scrutinizer tool developed in the Graph-Massivizer project.
Processing of graph and time series data, with a focus on increased scalability.
Graph-Scrutinizer offers three tools services:
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The Go-Network tool that
- implements deterministic algorithms for creating classic, synthetic graph;
- implements algorithms for creating random, synthetic graph; and
- implements numerous graph sampling algorithms.
-
The TS2G2 tool that
- implements several conversion algorithms for time series to graphs and for graphs to time series;
- provides functions for analyzing and visualizing the aforementioned time series and graphs; and
- provides a detailed demo for understanding the tool and underlying algorithms.
-
The Multi-Summaries tool that
- implements an efficient algorithm for computing and representing the full k-forward bisimulation of a graph in the form of a multi-summary;
- has been successfully tested on graphs with tens of billions of typed edges; and
- provides functions for analyzing and visualizing the generated multi-summaries and the process of creating them.
Each of our tools are meant to operate in a standalone manner, without any internal dependencies on each other.
The three tools are maintained in three separate repositories on GitHub:
- https://github.com/graph-massivizer/go-network
- https://github.com/graph-massivizer/ts2g2
- https://github.com/R-van-Bakel/Multi-Summaries
Graph-Scrutinizer is released as open source software under the Apache License, Version 2.0
The Graph-Scrutinizer predominantly uses three programming languages:
- Go (Go-Network)
- Python (TS2G2 and Multi-Summaries)
- C++ (Multi-Summaries)
The Graph-Scrutinizer tools offers BGOs that can be used when processing graphs in the Graph-Massivizer pipeline.
A detailed demo for the three Graph-Scrutinizer tools can be found on GitHub: https://github.com/R-van-Bakel/Graph-Scrutinizer_Demo_2.0