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NetworkX provides functions for applying different layout algorithms to graphs and visualizing the results using Matplotlib or other plotting libraries. Users can specify the desired layout algorithm when calling the drawing functions, allowing for flexible and customizable graph visualizations.
Microsoft Automatic Graph Layout, open-source .NET library (formerly called GLEE) for laying out graphs [30] NetworkX is a Python library for studying graphs and networks. Tulip, [31] an open-source data visualization tool; yEd, a graph editor with graph layout functionality [32] PGF/TikZ 3.0 with the graphdrawing package (requires LuaTeX). [33]
Force-directed graph drawing algorithms assign forces among the set of edges and the set of nodes of a graph drawing.Typically, spring-like attractive forces based on Hooke's law are used to attract pairs of endpoints of the graph's edges towards each other, while simultaneously repulsive forces like those of electrically charged particles based on Coulomb's law are used to separate all pairs ...
Graphviz (short for Graph Visualization Software) is a package of open-source tools initiated by AT&T Labs Research for drawing graphs (as in nodes and edges, not as in bar charts) specified in DOT language scripts having the file name extension "gv". It also provides libraries for software applications to use the tools.
Spectral layout is a class of algorithm for drawing graphs. The layout uses the eigenvectors of a matrix, such as the Laplace matrix of the graph, as Cartesian coordinates of the graph's vertices. The idea of the layout is to compute the two largest (or smallest) eigenvalues and corresponding eigenvectors of the Laplacian matrix of the graph ...
Graph-tool, a free Python module for manipulation and statistical analysis of graphs. NetworkX, an open source Python library for studying complex graphs. Tulip (software) is a free software in the domain of information visualisation capable of manipulating huge graphs (with more than 1.000.000 elements).
For a simple graph with vertex set U = {u 1, …, u n}, the adjacency matrix is a square n × n matrix A such that its element A ij is 1 when there is an edge from vertex u i to vertex u j, and 0 when there is no edge. [1]
For every pair of vertices in a connected graph, there exists at least one shortest path between the vertices, that is, there exists at least one path such that either the number of edges that the path passes through (for unweighted graphs) or the sum of the weights of the edges (for weighted graphs) is minimized. The betweenness centrality for ...