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Create Adj. Matrix w/ Edges Represented as TFNs

Source: R/IVFNs_and_TFNs.R
make_adj_matrix_w_tfns.Rd

This constructs an adjacency matrix with edges represented by triangular fuzzy numbers (TFNs) from an adjacency matrix of lower bounds, an adjacency matrix of modes, and an adjacency matrix of upper bounds

Usage

make_adj_matrix_w_tfns(
  lower = data.frame(),
  mode = data.frame(),
  upper = data.frame()
)

Arguments

lower

[list() or data.frame()]
An n x n adjacency matrix that represents the lower limits of edges in an FCM

mode

[list() or data.frame()]
An n x n adjacency matrix that represents the modes (most likely values) of edges in an FCM

upper

[list() or data.frame()]
An n x n adjacency matrix that represents the upper limits of edges in an FCM

Value

[adj_matrix_w_tfns]
An adjacency matrix (of class 'tfn') with edges represented as TFNs

Details

The input adjacency matrices must square n x n matrices with the same dimensions. The input can be either matrix, data.table, tibble, or data.table type objects, but the output will always be a data.frame. This is for output readability. data.table and tibble objects work logically, but their outputs require additional steps to parse from the user's perspective.

If the input matrices have named columns, those names will be carried over in the triangular adjacency matrix. Otherwise, generic node IDs will be used (C1, C2, ... Cn).

See also

Other triangular-fuzzy-numbers: create_tfn_fcm_from_conventional_fcm(), print.tfn(), subtract_tfn(), tfn()

Examples

make_adj_matrix_w_tfns(
  lower = matrix(data = c(0, 0.2, 0, 0.5), nrow = 2, ncol = 2),
  mode = matrix(data = c(0, 0.3, 0, 0.6), nrow = 2, ncol = 2),
  upper = matrix(data = c(0, 0.4, 0, 0.7), nrow = 2, ncol = 2)
)
#>               V1            V2
#> V1       0, 0, 0       0, 0, 0
#> V2 0.2, 0.3, 0.4 0.5, 0.6, 0.7

lower_adj_matrix <- data.frame(
  "A" = c(0, 0),
  "B" = c(0.4, 0)
)
mode_adj_matrix <- data.frame(
  "A" = c(0, 0),
  "B" = c(0.4, 0)
)
upper_adj_matrix <- data.frame(
  "A" = c(0, 0),
  "B" = c(0.6, 0)
)
make_adj_matrix_w_tfns(lower_adj_matrix, mode_adj_matrix, upper_adj_matrix)
#>         A             B
#> A 0, 0, 0 0.4, 0.4, 0.6
#> B 0, 0, 0       0, 0, 0