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PetriKit is a modular toolkit for Petri Net analysis. It allows the extraction of basic properties, extraction of invariants, and generation of reachability graph. Results can be formatted in plain text, HTML or XML files.
pyLastFM graph is commandline tool for creating a nice looking graph time graph from Last.fm profile data. It uses the audioscrobbler.net XML interface and can create very high resolution output images.
GUESS, or the Graph Exploration System, is a system and language for visualizing and manipulating graph structures and creating new visualization applications.
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sarface is a user-interface to the sysstat/sar database which inputs data from sar and plots to a live X11 graph via gnuplot. It mimics the cmd-line options from sar but can cross-plot any two or more stats and apply simple mathematical functions them.
FreeCeilo is an interface for Ceilometer CL-31.It works in offline mode. It plots backscatter intensity, cloud base graph and surface plot.It was tested and developed at SPACE, Thiruvananthapuram, and is implemented in CESS.
AGTK is a suite of software components for building tools for annotating linguistic signals,
time-series data which documents any kind of linguistic behavior (e.g. audio, video).
The internal data structures are based on annotation graphs.
A simple (~20 line python) O(n^6) algorithm for the traveling salesman problem that seems to do pretty well for most graphs; so well that I have not been able to find a graph which it does optimally solve. Those with spare cycles are welcome to help out.
GRINEdit is a graph, relation, interaction, network editor.
The graph visualizer 'graphviz' is very popular but it is not interactive.
The project aims to make interactive graphviz.
Togra is a high-level approach to 3D application scripting using Python and OpenGL. Rather than providing direct access to OpenGL calls, Togra allows users to script a call graph, then evaluates this call graph in C. This gives easy, fast 3D graphics.
C++ and Python based open source graph visualization and analysis software, primarily intended for use in the analysis of social networks (other applications are also conceivable).
sarplot provides automated graph generation from statistics generated by the sar (system activity recorder) utilitiy. It is intended as a drop-in utility that generates daily
and hourly graphs viewable through a web interface.
Python library to convert networks from/to many different formats, like the ones used in Pajek, Cytoscape and other popular graph formats like GML. It also includes support to integrate experimental data to the netowork.
A Java software for 3D visualization of graphs/networks. It implements many graph layout algorithms (such as force-directed methods), graph generators (such as scale-free networks) and graph modifiers. Most functions can be accessed through its GUI.
bitHull is a Simple unstructured data store-and-share mechanism. It is part experimental graph-based task/note/idea management system and part data aggregator.
boost_graph tried to wrap the C++ Boost Graph library in Python, providing graph algorithms like Breadth First Search, DFS, Shortest Path, Topological sort. This project is dead (http://bayleshanks.com/pamv1)
RISO: distributed, heterogeneous Bayesian belief networks. Belief network: a probability model defined on an acyclic directed graph; distributed: nodes can be on different hosts; and heterogeneous: allowing different types of conditional distributions.
e4Graph is a C++ library and a Tcl binding providing persistent, reliable, cross-platform storage for graph like structures. Please visit http://e4graph.sourceforge.net for more info.
Network Visualization is a mature part of computer science that is enjoying a good deal of growth, partially fueled by Bioinformatics. Network is a synonym for Graph, and both refer to a collection of nodes and edges.
This application is designed to solve problems of transshipment. This
problem of the graph theory consists in finding a negative stream on the
arcs which minimizes the total cost of the transport in a network
R(V,E,b,c) where :
- V = vertex
- E