Mendz.Graph.Representation is on GitHub and NuGet
If you like Mendz.Matrix and Mendz.Graph, you'll love Mendz.Graph.Representation.
Mendz.Matrix defines dense, DOK sparse and compressed matrices. Mendz.Graph defines a graph that implements the definition G = (V,E). Put them all together and you get graph representations like adjacency list, adjacency matrix, Laplacian matrix and what have you. These representations help in solving some of the problems with working on the raw graph data.
Mendz.Graph.Representation uses Mendz.Matrix and Mendz.Graph to provide graph representations that can be easily searched, traversed and operated on. Keys to these are the Graph's indexed vertices and indexed edges features, which provide quick and easy ways to consume and use graph data. You can use Mendz.Matrix features to operate on graph representations like transpose, addition, subtraction, multiplication and compression, for example.
Graphs can be represented as an AdjacenyList. You can also choose to represent graphs as matrices, which can be dense or sparse versions of the following:
NuGet it and learn the code at GitHub.
Mendz.Matrix defines dense, DOK sparse and compressed matrices. Mendz.Graph defines a graph that implements the definition G = (V,E). Put them all together and you get graph representations like adjacency list, adjacency matrix, Laplacian matrix and what have you. These representations help in solving some of the problems with working on the raw graph data.
Mendz.Graph.Representation uses Mendz.Matrix and Mendz.Graph to provide graph representations that can be easily searched, traversed and operated on. Keys to these are the Graph's indexed vertices and indexed edges features, which provide quick and easy ways to consume and use graph data. You can use Mendz.Matrix features to operate on graph representations like transpose, addition, subtraction, multiplication and compression, for example.
Graphs can be represented as an AdjacenyList. You can also choose to represent graphs as matrices, which can be dense or sparse versions of the following:
- ConnectionMatrix - represents a connection matrix.
- AdjacencyMatrix - represents an adjacency matrix.
- WeightedAdjacencyMatrix - represents a weighted adjacency matrix.
- SeidelAdjacencyMatrix - represents a Seidel adjacency matrix.
- GenericAdjacencyMatrix - represents a generic adjacency matrix.
- LaplacianMatrix - represents a Laplacian matrix.
- DegreeMatrix - represents a degree matrix.
- InDegreeMatrix - represents an indegree matrix.
- OutDegreeMatrix - represents an outdegree matrix.
- IncidenceMatrix - represents an incidence matrix.
NuGet it and learn the code at GitHub.
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