Given a list of adj. matrices of different sizes, transforms the inputs into adj. matrices of the same size with 0 values added where edges are undefined or not included in maps.
Solves the problem where Map 1 has nodes A and B but Map 2 has nodes B and C and need to analyse them both together.
Usage
standardize_adj_matrices(adj_matrices = list())Arguments
- adj_matrices
[
list()]
A single adjacency matrix or a list of adjacency matrices (n x n) representing FCMs. Matrices can have conventional edge weights, IVFN edge weights or TFN edge weights.
Value
[list()]
A list of adjacency matrices constructed from the
input adj. matrices, that contain the same concepts (and dimensions).
Rows/Columns of added concepts are all 0's.
Examples
# Standardize Conventional FCMs
adj_matrix_1 <- data.frame(
"A" = c(0, 0),
"B" = c(1, 0)
)
adj_matrix_2 <- data.frame(
"A" = c(0, 0, 0),
"B" = c(0.25, 0, 1),
"C" = c(0, 0.7, 0)
)
adj_matrix_3 <- data.frame(
"B" = c(0, 0),
"D" = c(0.75, 0)
)
adj_matrix_4 <- data.frame(
"A" = c(0, 0, 0.3, 0),
"B" = c(0.5, 0, 0, 0.6),
"E" = c(0, 0, 0, 0),
"F" = c(1, 0, 1, 0)
)
adj_matrices_w_different_concepts <- list(
adj_matrix_1, adj_matrix_2, adj_matrix_3, adj_matrix_4
)
standardize_adj_matrices(adj_matrices_w_different_concepts)
#> [[1]]
#> A B C D E F
#> 1 0 1 0 0 0 0
#> 2 0 0 0 0 0 0
#> 3 0 0 0 0 0 0
#> 4 0 0 0 0 0 0
#> 5 0 0 0 0 0 0
#> 6 0 0 0 0 0 0
#>
#> [[2]]
#> A B C D E F
#> 1 0 0.25 0.0 0 0 0
#> 2 0 0.00 0.7 0 0 0
#> 3 0 1.00 0.0 0 0 0
#> 4 0 0.00 0.0 0 0 0
#> 5 0 0.00 0.0 0 0 0
#> 6 0 0.00 0.0 0 0 0
#>
#> [[3]]
#> A B C D E F
#> 1 0 0 0 0.00 0 0
#> 2 0 0 0 0.75 0 0
#> 3 0 0 0 0.00 0 0
#> 4 0 0 0 0.00 0 0
#> 5 0 0 0 0.00 0 0
#> 6 0 0 0 0.00 0 0
#>
#> [[4]]
#> A B C D E F
#> 1 0.0 0.5 0 0 0 1
#> 2 0.0 0.0 0 0 0 0
#> 3 0.0 0.0 0 0 0 0
#> 4 0.0 0.0 0 0 0 0
#> 5 0.3 0.0 0 0 0 1
#> 6 0.0 0.6 0 0 0 0
#>
# Standardize IVFN FCMs
adj_matrix_1_lower <- data.frame(
"A" = c(0, 0),
"B" = c(0.8, 0)
)
adj_matrix_1_upper <- data.frame(
"A" = c(0, 0),
"B" = c(1, 0)
)
ivfn_adj_matrix_1 <- make_adj_matrix_w_ivfns(
adj_matrix_1_lower, adj_matrix_1_upper
)
adj_matrix_2_lower <- data.frame(
"A" = c(0, 0, 0),
"B" = c(0.1, 0, 0.8),
"C" = c(0, 0.6, 0)
)
adj_matrix_2_upper <- data.frame(
"A" = c(0, 0, 0),
"B" = c(0.3, 0, 1),
"C" = c(0, 0.8, 0)
)
ivfn_adj_matrix_2 <- make_adj_matrix_w_ivfns(
adj_matrix_2_lower, adj_matrix_2_upper
)
adj_matrices_w_different_concepts <- list(
ivfn_adj_matrix_1, ivfn_adj_matrix_2
)
standardize_adj_matrices(adj_matrices_w_different_concepts)
#> [[1]]
#> A B C
#> 1 0, 0 0.8, 1.0 0, 0
#> 2 0, 0 0, 0 0, 0
#> 3 0, 0 0, 0 0, 0
#>
#> [[2]]
#> A B C
#> 1 0, 0 0.1, 0.3 0, 0
#> 2 0, 0 0, 0 0.6, 0.8
#> 3 0, 0 0.8, 1.0 0, 0
#>
# Standardize TFN FCMs
adj_matrix_1_lower <- data.frame(
"A" = c(0, 0),
"B" = c(0.8, 0)
)
adj_matrix_1_mode <- data.frame(
"A" = c(0, 0),
"B" = c(0.9, 0)
)
adj_matrix_1_upper <- data.frame(
"A" = c(0, 0),
"B" = c(1, 0)
)
tfn_adj_matrix_1 <- make_adj_matrix_w_tfns(
adj_matrix_1_lower, adj_matrix_1_mode, adj_matrix_1_upper
)
adj_matrix_2_lower <- data.frame(
"A" = c(0, 0, 0),
"B" = c(0.1, 0, 0.8),
"C" = c(0, 0.6, 0)
)
adj_matrix_2_mode <- data.frame(
"A" = c(0, 0, 0),
"B" = c(0.2, 0, 0.9),
"C" = c(0, 0.7, 0)
)
adj_matrix_2_upper <- data.frame(
"A" = c(0, 0, 0),
"B" = c(0.3, 0, 1),
"C" = c(0, 0.8, 0)
)
tfn_adj_matrix_2 <- make_adj_matrix_w_tfns(
adj_matrix_2_lower, adj_matrix_2_mode, adj_matrix_2_upper
)
adj_matrices_w_different_concepts <- list(
ivfn_adj_matrix_1, ivfn_adj_matrix_2
)
standardize_adj_matrices(adj_matrices_w_different_concepts)
#> [[1]]
#> A B C
#> 1 0, 0 0.8, 1.0 0, 0
#> 2 0, 0 0, 0 0, 0
#> 3 0, 0 0, 0 0, 0
#>
#> [[2]]
#> A B C
#> 1 0, 0 0.1, 0.3 0, 0
#> 2 0, 0 0, 0 0.6, 0.8
#> 3 0, 0 0.8, 1.0 0, 0
#>