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On top of GraphLab, several implemented libraries of algorithms: Topic modeling - contains applications like LDA, which can be used to cluster documents and extract topical representations. [4] Graph analytics - contains applications like pagerank and triangle counting, which can be applied to general graphs to estimate community structure. [5]
GrGen.NET, the graph rewrite generator, a graph transformation tool emitting C#-code or .NET-assemblies. GROOVE, a Java-based tool set for editing graphs and graph transformation rules, exploring the state spaces of graph grammars, and model checking those state spaces; can also be used as a graph transformation engine.
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 ...
A modified Coffman–Graham scheduling algorithm is then used to find a layout that would fit in a given space. More detailed description of the algorithm can be found in U.S. patent 7,932,907. At some time, it did not support a wide range of different layout algorithms, unlike, for instance, GraphViz or GUESS.
A common example of a graph-based pathfinding algorithm is Dijkstra's algorithm. [3] This algorithm begins with a start node and an "open set" of candidate nodes. At each step, the node in the open set with the lowest distance from the start is examined.
3D version of Prim's algorithm. Vertical layers are labeled 1 through 4 from bottom to top. Stairs up are indicated with "/"; stairs down with "\", and stairs up-and-down with "x". Source code is included with the image description. Other algorithms exist that require only enough memory to store one line of a 2D maze or one plane of a 3D maze.
The traditional flood-fill algorithm takes three parameters: a start node, a target color, and a replacement color. The algorithm looks for all nodes in the array that are connected to the start node by a path of the target color and changes them to the replacement color.
A graph, containing vertices and connecting edges, is constructed from relevant input data. The vertices contain information required by the comparison heuristic, while the edges indicate connected 'neighbors'. An algorithm traverses the graph, labeling the vertices based on the connectivity and relative values of their neighbors.