Farthest point sampling

Farthest point sampling returns a reordering of the metric space P = p_1, ..., p_k, such that each p_i is the farthest point from the first i-1 points.

farthest_point_sampling(mat, metric = "precomputed", k = nrow(mat),
  initial_point_index = 1L, return_clusters = FALSE)

Arguments

mat	Original distance matrix
metric	Distance metric to use (either "precomputed" or a metric from rdist)
k	Number of points to sample
initial_point_index	Index of p_1
return_clusters	Should the indices of the closest farthest points be returned?

Examples

# generate data
df <- matrix(runif(200), ncol = 2)
dist_mat <- pdist(df)
# farthest point sampling
fps <- farthest_point_sampling(dist_mat)
fps2 <- farthest_point_sampling(df, metric = "euclidean")
all.equal(fps, fps2)
#> [1] TRUE
# have a look at the fps distance matrix
rdist(df[fps[1:5], ])
#>           1         2         3         4
#> 2 1.0924360                              
#> 3 0.9280582 0.8499785                    
#> 4 0.8029144 0.8977409 1.3558406          
#> 5 0.5409166 0.5515509 0.7071422 0.6487099
dist_mat[fps, fps][1:5, 1:5]
#>           [,1]      [,2]      [,3]      [,4]      [,5]
#> [1,] 0.0000000 1.0924360 0.9280582 0.8029144 0.5409166
#> [2,] 1.0924360 0.0000000 0.8499785 0.8977409 0.5515509
#> [3,] 0.9280582 0.8499785 0.0000000 1.3558406 0.7071422
#> [4,] 0.8029144 0.8977409 1.3558406 0.0000000 0.6487099
#> [5,] 0.5409166 0.5515509 0.7071422 0.6487099 0.0000000