Modifies the input matrix X to ensure that the distance between any two occurrences
of the same integer is at least a distance d, by swapping one of the occurrences with a
candidate cell of a different integer. The function starts with starting_dist = 3 and increases it
by 1 until the algorithm no longer converges or stop_iter iterations have been performed.
This version evaluates candidate swaps using both the mean pairwise distance and a centrality penalty,
and it uses candidate sampling to reduce computation.
Usage
swap_pairs(
X,
starting_dist = 3,
stop_iter = 10,
lambda = 0.5,
dist_method = "euclidean",
candidate_sample_size = 4
)Arguments
- X
A matrix of integers.
- starting_dist
The minimum starting distance to enforce between pairs of occurrences of the same integer. Default is 3.
- stop_iter
The maximum number of iterations to perform. Default is 50.
- lambda
A tuning parameter for the centrality penalty. Default is 0.1.
- dist_method
The method used for distance calculation. Options are "euclidean" (default) and "manhattan".
- candidate_sample_size
Maximum number of candidate cells to evaluate per swap. Default is 5.
Value
A list containing:
- optim_design
The modified matrix.
- designs
A list of all intermediate designs, starting from the input matrix.
- distances
A list of all pair distances for each intermediate design.
- min_distance
The minimum distance between pairs of occurrences of the same integer in the final design.
- pairwise_distance
A data frame with the pairwise distances for the final design.
- rows_incidence
A vector recording the number of rows with repeated integers for each iteration.
Examples
set.seed(123)
X <- matrix(sample(c(rep(1:10, 2), 11:50), replace = FALSE), ncol = 10)
B <- swap_pairs(
X,
starting_dist = 3,
stop_iter = 50,
lambda = 0.5,
dist_method = "euclidean",
candidate_sample_size = 3
)
B$optim_design
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,] 6 1 24 44 27 19 15 3 39 2
#> [2,] 3 45 20 32 48 29 43 33 7 6
#> [3,] 10 4 36 30 46 28 14 9 22 10
#> [4,] 7 2 8 31 16 40 47 17 34 5
#> [5,] 42 38 5 26 49 50 35 37 1 8
#> [6,] 9 21 12 23 25 13 41 11 4 18