Documentation
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Overview ¶
Package spectral provides graph spectral analysis functions.
Index ¶
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
This section is empty.
Types ¶
type Laplacian ¶
type Laplacian struct {
// Matrix holds the Laplacian matrix.
mat.Matrix
// Nodes holds the input graph nodes.
Nodes []graph.Node
// Index is a mapping from the graph
// node IDs to row and column indices.
Index map[int64]int
}
Laplacian is a graph Laplacian matrix.
func NewLaplacian ¶
func NewLaplacian(g graph.Undirected) Laplacian
NewLaplacian returns a Laplacian matrix for the simple undirected graph g. The Laplacian is defined as D-A where D is a diagonal matrix holding the degree of each node and A is the graph adjacency matrix of the input graph. If g contains self edges, NewLaplacian will panic.
func NewRandomWalkLaplacian ¶
NewRandomWalkLaplacian returns a damp-scaled random walk Laplacian matrix for the simple graph g. The random walk Laplacian is defined as I-D^(-1)A where D is a diagonal matrix holding the degree of each node and A is the graph adjacency matrix of the input graph. If g contains self edges, NewRandomWalkLaplacian will panic.
func NewSymNormLaplacian ¶
func NewSymNormLaplacian(g graph.Undirected) Laplacian
NewSymNormLaplacian returns a symmetric normalized Laplacian matrix for the simple undirected graph g. The normalized Laplacian is defined as I-D^(-1/2)AD^(-1/2) where D is a diagonal matrix holding the degree of each node and A is the graph adjacency matrix of the input graph. If g contains self edges, NewSymNormLaplacian will panic.
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