bilateral_smoother: Bilateral Spatial Smoother

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

Bilateral Spatial Smoother

Description

This function computes a bilateral smoothing of the input data, which combines spatial and feature information to provide a smoothed representation of the data.

Usage

bilateral_smoother(
  coord_mat,
  feature_mat,
  nnk = 27,
  s_sigma = 2.5,
  f_sigma = 0.7,
  stochastic = FALSE
)

Arguments

coord_mat	A matrix with the spatial coordinates of the data points, where each row represents a point and each column represents a coordinate dimension.
feature_mat	A matrix with the feature vectors of the data points, where each row represents a point and each column represents a feature dimension.
nnk	The number of nearest neighbors to consider for smoothing (default: 27).
s_sigma	The spatial bandwidth in standard deviations (default: 2.5).
f_sigma	The normalized feature bandwidth in standard deviations (default: 0.7).
stochastic	A logical value indicating whether to make the resulting adjacency matrix doubly stochastic (default: FALSE).

Value

A sparse adjacency matrix representing the smoothed data.

Examples

coord_mat <- as.matrix(expand.grid(1:10, 1:10))
feature_mat <- matrix(rnorm(100*10), 100, 10)
S <- bilateral_smoother(coord_mat, feature_mat, nnk=8)

bbuchsbaum/graphweights documentation built on April 4, 2024, 7:19 p.m.