Perturb a binary graph probabilistically
make_perturbed_graph(
x,
prob_tot = NULL,
prob_0_to_1 = 0,
prob_1_to_0 = 0,
combined = FALSE,
replace = FALSE,
diag = FALSE
)graph of class igraph, network, or matrix
probability of any edge to change (from 1 to 0 or 0 to 1)
probability of any 0 edge to change to a 1
probability of any 0 edge to change to a 1
logical, see details
logical, whether to draw the cells to be changed with replacement
logical, should the diagonal (self-loops) be allowed to change?
the perturbed graph
Given a binary (ie. non-weighted) graph, change some proportion of its edges from 0 to 1 or 1 to 0. There are several ways of doing this:
When prob_tot is specified and combined is set to FALSE,
all edges in the graph have the same probability of changing. In this case,
prob_0_to 1 and prob_1_to_0 are ignored and, hence, no distinction
is made between edges with value 0 or with value 1.
This will ignore any choice of prob_0_to 1 and prob_1_to_0.
When prob_tot is NULL, edges with value 0 will change to a 1
with probability prob_0_to 1 and edges with value 1 will change to a 0
with probability prob_1_to 0.
When prob_tot is specified and combined is set to TRUE,
first edges with value 0 will change to a 1 with probability prob_0_to 1
and edges with value 1 will change to a 0 with probability prob_1_to 0.
After that, the edges in the resulting graph will be perturbated with
probability prob_tot (potentially reversing some of the previous changes).
The replace argument allows for edges to be drawn multiple times.
This means that fewer edges will change, since the same edge might change from
a 0 to a 1 multiple times (or from a 1 to a 0).
This is likely rarely useful.
The resulting graph will have the same class as has x.
g <- snafun::create_random_graph(20, "gnm", m = 100)
make_perturbed_graph(g, prob_tot = .3)
#> IGRAPH d94ddf5 D--- 20 152 --
#> + edges from d94ddf5:
#> [1] 1-> 5 1-> 7 1->11 1->16 1->17 1->18 2-> 1 2->12 2->15 2->18
#> [11] 2->19 3-> 2 3-> 6 3-> 8 3-> 9 3->11 3->13 3->14 3->20 4-> 8
#> [21] 4->10 4->11 4->14 4->17 4->19 5-> 1 5-> 2 5-> 8 5->10 5->15
#> [31] 6-> 1 6-> 3 6-> 5 6-> 8 6-> 9 6->10 6->13 6->14 6->19 6->20
#> [41] 7-> 2 7-> 3 7-> 4 7-> 6 7-> 8 7->16 7->20 8-> 2 8-> 3 8-> 4
#> [51] 8-> 7 8->12 8->13 8->14 8->16 8->20 9-> 2 9-> 3 9-> 5 9-> 6
#> [61] 9-> 7 9->12 9->13 9->17 9->18 9->20 10-> 7 10->13 10->15 10->18
#> [71] 11-> 3 11-> 5 11-> 6 11-> 9 11->10 11->14 11->17 11->18 12-> 1 12-> 3
#> [81] 12-> 4 12-> 5 12-> 6 12->14 12->17 13-> 2 13-> 5 13-> 9 13->10 13->12
#> + ... omitted several edges
# prob_0_to_1 is ignored
make_perturbed_graph(g, prob_tot = .3, prob_0_to_1 = 1)
#> IGRAPH d95059c D--- 20 154 --
#> + edges from d95059c:
#> [1] 1-> 2 1-> 9 1->12 1->13 1->17 1->19 1->20 2-> 1 2-> 3 2-> 6
#> [11] 2-> 8 2->10 2->18 2->19 2->20 3-> 2 3-> 6 3->10 3->13 3->14
#> [21] 3->17 3->18 3->19 3->20 4-> 1 4-> 3 4->15 4->16 4->19 4->20
#> [31] 5-> 1 5-> 4 5-> 6 5->13 5->14 5->15 5->17 5->18 5->19 6-> 3
#> [41] 6-> 7 6-> 8 6->10 6->13 6->20 7-> 3 7-> 5 7-> 8 7-> 9 7->10
#> [51] 7->11 7->12 7->15 7->17 7->19 8-> 2 8-> 3 8-> 4 8-> 6 8->12
#> [61] 8->14 8->15 8->17 8->18 8->19 8->20 9-> 4 9-> 5 9-> 6 9->12
#> [71] 9->13 9->16 9->18 9->20 10-> 2 10-> 7 10-> 9 10->13 10->15 10->16
#> [81] 10->19 11-> 3 11-> 6 11-> 9 11->10 12-> 2 12-> 5 12-> 9 12->13 12->17
#> + ... omitted several edges
# prob_0_to_1 is used first, then prob_tot
make_perturbed_graph(g, prob_tot = .3, prob_0_to_1 = 1, combined = TRUE)
#> IGRAPH d9527d4 D--- 20 266 --
#> + edges from d9527d4:
#> [1] 1-> 2 1-> 3 1-> 4 1-> 5 1-> 6 1-> 7 1-> 8 1-> 9 1->12 1->13 1->15 1->16
#> [13] 1->17 1->19 1->20 2-> 1 2-> 3 2-> 7 2-> 9 2->12 2->13 2->14 2->16 2->17
#> [25] 2->20 3-> 2 3-> 4 3-> 5 3-> 6 3-> 7 3-> 9 3->12 3->13 3->14 3->16 3->17
#> [37] 3->18 3->19 3->20 4-> 2 4-> 3 4-> 5 4-> 6 4-> 7 4-> 8 4-> 9 4->11 4->13
#> [49] 4->14 4->15 4->17 4->19 4->20 5-> 2 5-> 7 5-> 8 5->12 5->13 5->14 5->16
#> [61] 5->17 5->18 5->20 6-> 2 6-> 3 6-> 4 6-> 5 6-> 7 6->10 6->11 6->12 6->13
#> [73] 6->14 6->15 6->16 6->17 6->18 6->19 6->20 7-> 1 7-> 2 7-> 4 7-> 6 7-> 8
#> [85] 7-> 9 7->10 7->11 7->12 7->13 7->14 7->15 7->16 7->17 7->18 7->19 8-> 1
#> [97] 8-> 2 8-> 3 8-> 4 8-> 6 8-> 7 8->11 8->13 8->17 8->18 8->20 9-> 2 9-> 6
#> + ... omitted several edges
make_perturbed_graph(snafun::to_matrix(g), prob_tot = .3, prob_0_to_1 = 1)
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 0 1 0 0 0 0 0 1 0 0 0 0 1
#> [2,] 0 0 0 0 1 1 0 1 0 1 0 1 0
#> [3,] 0 0 0 1 1 0 0 0 1 0 0 0 0
#> [4,] 0 1 0 0 1 0 0 0 0 0 1 0 0
#> [5,] 1 1 0 0 0 0 0 0 0 0 1 1 1
#> [6,] 0 1 0 1 0 0 0 1 0 0 1 0 0
#> [7,] 1 1 1 0 0 0 0 1 0 1 1 0 0
#> [8,] 0 1 0 0 0 0 0 0 0 0 0 0 0
#> [9,] 0 0 0 1 1 0 0 0 0 0 0 1 0
#> [10,] 0 1 0 0 0 0 0 0 1 0 0 0 1
#> [11,] 0 0 1 0 1 0 1 1 0 1 0 0 0
#> [12,] 0 0 0 0 1 0 1 1 1 1 0 0 0
#> [13,] 0 1 1 0 1 0 0 0 0 0 0 1 0
#> [14,] 1 1 1 1 0 1 0 0 1 0 1 0 1
#> [15,] 0 1 1 0 0 0 0 1 0 0 0 0 0
#> [16,] 0 0 1 1 0 1 0 0 0 0 1 0 1
#> [17,] 1 0 1 1 0 0 0 1 1 0 1 0 0
#> [18,] 0 0 0 1 0 1 1 0 0 1 1 0 0
#> [19,] 0 1 0 1 0 1 0 0 1 1 1 0 0
#> [20,] 0 0 0 0 1 1 0 0 0 0 0 0 0
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20]
#> [1,] 1 0 1 0 0 1 0
#> [2,] 1 0 1 0 1 1 0
#> [3,] 0 0 1 0 1 0 0
#> [4,] 0 0 1 0 0 0 0
#> [5,] 1 1 1 1 1 1 0
#> [6,] 0 0 1 0 1 1 1
#> [7,] 0 0 1 0 0 1 0
#> [8,] 1 0 0 1 0 1 0
#> [9,] 0 0 0 0 0 0 0
#> [10,] 1 1 0 0 0 1 0
#> [11,] 1 0 0 1 0 0 0
#> [12,] 1 0 1 0 1 0 0
#> [13,] 1 0 1 0 1 1 1
#> [14,] 0 1 0 1 0 0 1
#> [15,] 0 0 1 0 1 1 0
#> [16,] 1 1 0 0 1 1 0
#> [17,] 1 0 0 0 1 1 1
#> [18,] 0 1 0 0 0 0 1
#> [19,] 0 1 0 1 1 0 0
#> [20,] 0 0 1 1 0 0 0
make_perturbed_graph(snafun::to_network(g), prob_tot = .3, prob_0_to_1 = 1)
#> Network attributes:
#> vertices = 20
#> directed = TRUE
#> hyper = FALSE
#> loops = FALSE
#> multiple = FALSE
#> bipartite = FALSE
#> total edges= 160
#> missing edges= 0
#> non-missing edges= 160
#>
#> Vertex attribute names:
#> vertex.names
#>
#> No edge attributes