Create a spatial weights matrix

Source: R/spatial_weights_matrix.R

Creates a spatial weights matrix by multiplying an adjacency (connectivity) matrix (see connectivity_matrix()) and an edges weights matrix (see edges_weights_matrix()). Resulting spatial weights equal to 0 will be replaced by 4 x max(w), where max(w) is the maximal weight in the matrix.

spatial_weights_matrix(x, y)

Arguments

x

an adjacency matrix of dimensions n x n, where n is the number of nodes (sites). The output of connectivity_matrix().

y

an edges weight matrix of dimensions n x n, where n is the number of nodes (sites). The output of edges_weights_matrix().

Value

A spatial weights matrix of dimensions n x n, where n is the number of nodes (sites).

Examples

# Import Adour sites ----
path_to_file <- system.file("extdata", "adour_survey_sampling.csv", 
                            package = "chessboard")
adour_sites <- read.csv(path_to_file)

# Select the 15 first sites ----
adour_sites <- adour_sites[1:15, ]

# Create node labels ----
adour_sites <- create_node_labels(adour_sites, 
                                  location = "location", 
                                  transect = "transect", 
                                  quadrat  = "quadrat")

# Create edges based on the pawn move (directed network) ----
adour_edges <- create_edge_list(adour_sites, method = "pawn", 
                                directed = TRUE)

# Get connectivity matrix ----
adour_adjacency <- connectivity_matrix(adour_edges)

# Convert sites to sf object (POINTS) ----
adour_sites_sf <- sf::st_as_sf(adour_sites, 
                               coords = c("longitude", "latitude"),
                               crs = "epsg:2154")

# Compute distances between pairs of sites along the Adour river ----
adour_dists <- distance_euclidean(adour_sites_sf)

# Create Edges weights matrix ----
adour_weights <- edges_weights_matrix(adour_dists)

# Create Spatial weights matrix ----
spatial_weights_matrix(adour_adjacency, adour_weights)
#>          1-1       1-2       1-3       1-4       1-5      2-1       2-2
#> 1-1 10001.88  2500.469 10001.876 10001.876 10001.876 10001.88 10001.876
#> 1-2 10001.88 10001.876  2500.469 10001.876 10001.876 10001.88 10001.876
#> 1-3 10001.88 10001.876 10001.876  2500.469 10001.876 10001.88 10001.876
#> 1-4 10001.88 10001.876 10001.876 10001.876  2500.469 10001.88 10001.876
#> 1-5 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88 10001.876
#> 2-1 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88  2500.469
#> 2-2 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88 10001.876
#> 2-3 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88 10001.876
#> 2-4 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88 10001.876
#> 2-5 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88 10001.876
#> 3-1 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88 10001.876
#> 3-2 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88 10001.876
#> 3-3 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88 10001.876
#> 3-4 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88 10001.876
#> 3-5 10001.88 10001.876 10001.876 10001.876 10001.876 10001.88 10001.876
#>           2-3       2-4       2-5      3-1       3-2       3-3       3-4
#> 1-1 10001.876 10001.876 10001.876 10001.88 10001.876 10001.876 10001.876
#> 1-2 10001.876 10001.876 10001.876 10001.88 10001.876 10001.876 10001.876
#> 1-3 10001.876 10001.876 10001.876 10001.88 10001.876 10001.876 10001.876
#> 1-4 10001.876 10001.876 10001.876 10001.88 10001.876 10001.876 10001.876
#> 1-5 10001.876 10001.876 10001.876 10001.88 10001.876 10001.876 10001.876
#> 2-1 10001.876 10001.876 10001.876 10001.88 10001.876 10001.876 10001.876
#> 2-2  2500.469 10001.876 10001.876 10001.88 10001.876 10001.876 10001.876
#> 2-3 10001.876  2500.469 10001.876 10001.88 10001.876 10001.876 10001.876
#> 2-4 10001.876 10001.876  2500.469 10001.88 10001.876 10001.876 10001.876
#> 2-5 10001.876 10001.876 10001.876 10001.88 10001.876 10001.876 10001.876
#> 3-1 10001.876 10001.876 10001.876 10001.88  2500.469 10001.876 10001.876
#> 3-2 10001.876 10001.876 10001.876 10001.88 10001.876  2500.469 10001.876
#> 3-3 10001.876 10001.876 10001.876 10001.88 10001.876 10001.876  2500.469
#> 3-4 10001.876 10001.876 10001.876 10001.88 10001.876 10001.876 10001.876
#> 3-5 10001.876 10001.876 10001.876 10001.88 10001.876 10001.876 10001.876
#>           3-5
#> 1-1 10001.876
#> 1-2 10001.876
#> 1-3 10001.876
#> 1-4 10001.876
#> 1-5 10001.876
#> 2-1 10001.876
#> 2-2 10001.876
#> 2-3 10001.876
#> 2-4 10001.876
#> 2-5 10001.876
#> 3-1 10001.876
#> 3-2 10001.876
#> 3-3 10001.876
#> 3-4  2500.469
#> 3-5 10001.876