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Overview

The neighborweights package provides a collection of functions for constructing adjacency matrices based on spatial and feature-based similarity between data points. It enables users to analyze and visualize complex data relationships by creating spatial and feature-weighted adjacency matrices using various methods.

Installation

You can install the neighborweights package from GitHub with:

# install.packages("devtools")
devtools::install_github("bbuchsbaum/neighborweights")

Usage

Here’s a basic example demonstrating how to create a spatial adjacency matrix using the spatial_adjacency function:

library(neighborweights)

# Generate random coordinates
coord_mat <- matrix(runif(20), nrow=10, ncol=2)

# Calculate the spatial adjacency matrix
spatial_mat <- spatial_adjacency(coord_mat, nnk=5, sigma=1)

# Inspect the resulting matrix
print(spatial_mat)
#> 10 x 10 sparse Matrix of class "dgCMatrix"
#>                                              
#>  [1,] 0.2 0.1 .   .   0.2 .   0.2 0.2 .   0.2
#>  [2,] 0.1 0.2 .   .   0.2 0.2 .   .   0.2 .  
#>  [3,] .   .   0.2 0.2 .   0.1 .   .   0.1 0.1
#>  [4,] .   .   0.2 0.2 .   0.2 .   .   0.2 0.1
#>  [5,] 0.2 0.2 .   .   0.2 .   0.1 0.1 .   .  
#>  [6,] .   0.2 0.1 0.2 .   0.2 .   .   0.2 0.1
#>  [7,] 0.2 .   .   .   0.1 .   0.2 0.2 0.1 0.2
#>  [8,] 0.2 .   .   .   0.1 .   0.2 0.2 0.1 0.2
#>  [9,] .   0.2 0.1 0.2 .   0.2 0.1 0.1 0.2 0.2
#> [10,] 0.2 .   0.1 0.1 .   0.1 0.2 0.2 0.2 0.2

For more advanced usage and additional examples, please refer to the package documentation and vignettes (coming soon).

Albers theme

This package uses the albersdown theme. Existing vignette theme hooks are replaced so albers.css and local albers.js render consistently on CRAN and GitHub Pages. The defaults are configured via params$family and params$preset (family = ‘teal’, preset = ‘homage’). The pkgdown site uses template: { package: albersdown } together with generated pkgdown/extra.css and pkgdown/extra.js so the theme is linked and activated on site pages.