spatial_laplacian: Compute the spatial Laplacian matrix of a coordinate matrix

In bbuchsbaum/neighborweights: Constructing Adjacency Matrices Based on Spatial and Feature Similarity

Compute the spatial Laplacian matrix of a coordinate matrix

Description

This function computes the spatial Laplacian matrix of a given coordinate matrix using specified parameters.

Usage

spatial_laplacian(
  coord_mat,
  dthresh = 1.42,
  nnk = 27,
  weight_mode = c("binary", "heat"),
  sigma = dthresh/2,
  normalized = TRUE,
  stochastic = FALSE
)

Arguments

coord_mat	A numeric matrix representing coordinates
dthresh	Numeric, the distance threshold for adjacency (default is 1.42)
nnk	Integer, the number of nearest neighbors for adjacency (default is 27)
weight_mode	Character, the mode for computing weights, either "binary" or "heat" (default is "binary")
sigma	Numeric, the sigma parameter for the heat kernel (default is dthresh/2)
normalized	Logical, whether the adjacency matrix should be normalized (default is TRUE)
stochastic	Logical, whether the adjacency matrix should be stochastic (default is FALSE)

Value

A sparse symmetric matrix representing the computed spatial Laplacian

Examples

# Create an example coordinate matrix
coord_mat <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 3, ncol = 2)

# Compute the spatial Laplacian matrix using the binary weight mode
result <- spatial_laplacian(coord_mat, dthresh = 1.42, nnk = 27, weight_mode = "binary")

bbuchsbaum/neighborweights documentation built on April 1, 2024, 8:41 p.m.