Convert igraph objects to adjacency or edge list matrices
Source:R/conversion.R
as.matrix.igraph.RdGet adjacency or edgelist representation of the network stored as an
igraph object.
Value
Depending on the value of matrix.type either a square
adjacency matrix or a two-column numeric matrix representing the edgelist.
Details
If matrix.type is "edgelist", then a two-column numeric edge list
matrix is returned. The value of attrname is ignored.
If matrix.type is "adjacency", then a square adjacency matrix is
returned. For adjacency matrices, you can use the attr keyword argument
to use the values of an edge attribute in the matrix cells. See the
documentation of as_adjacency_matrix for more details.
Other arguments passed through ... are passed to either
as_adjacency_matrix() or as_edgelist()
depending on the value of matrix.type.
See also
Other conversion:
as_adj_list(),
as_adjacency_matrix(),
as_biadjacency_matrix(),
as_data_frame(),
as_directed(),
as_edgelist(),
as_graphnel(),
as_long_data_frame(),
graph_from_adj_list(),
graph_from_graphnel()
Examples
g <- make_graph("zachary")
as.matrix(g, "adjacency")
#> 34 x 34 sparse Matrix of class "dgCMatrix"
#>
#> [1,] . 1 1 1 1 1 1 1 1 . 1 1 1 1 . . . 1 . 1 . 1 . . . . . . . . . 1 . .
#> [2,] 1 . 1 1 . . . 1 . . . . . 1 . . . 1 . 1 . 1 . . . . . . . . 1 . . .
#> [3,] 1 1 . 1 . . . 1 1 1 . . . 1 . . . . . . . . . . . . . 1 1 . . . 1 .
#> [4,] 1 1 1 . . . . 1 . . . . 1 1 . . . . . . . . . . . . . . . . . . . .
#> [5,] 1 . . . . . 1 . . . 1 . . . . . . . . . . . . . . . . . . . . . . .
#> [6,] 1 . . . . . 1 . . . 1 . . . . . 1 . . . . . . . . . . . . . . . . .
#> [7,] 1 . . . 1 1 . . . . . . . . . . 1 . . . . . . . . . . . . . . . . .
#> [8,] 1 1 1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> [9,] 1 . 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . 1 1
#> [10,] . . 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
#> [11,] 1 . . . 1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> [12,] 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> [13,] 1 . . 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> [14,] 1 1 1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
#> [15,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1
#> [16,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1
#> [17,] . . . . . 1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> [18,] 1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> [19,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1
#> [20,] 1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
#> [21,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1
#> [22,] 1 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
#> [23,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1
#> [24,] . . . . . . . . . . . . . . . . . . . . . . . . . 1 . 1 . 1 . . 1 1
#> [25,] . . . . . . . . . . . . . . . . . . . . . . . . . 1 . 1 . . . 1 . .
#> [26,] . . . . . . . . . . . . . . . . . . . . . . . 1 1 . . . . . . 1 . .
#> [27,] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . . . 1
#> [28,] . . 1 . . . . . . . . . . . . . . . . . . . . 1 1 . . . . . . . . 1
#> [29,] . . 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . 1
#> [30,] . . . . . . . . . . . . . . . . . . . . . . . 1 . . 1 . . . . . 1 1
#> [31,] . 1 . . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . 1 1
#> [32,] 1 . . . . . . . . . . . . . . . . . . . . . . . 1 1 . . 1 . . . 1 1
#> [33,] . . 1 . . . . . 1 . . . . . 1 1 . . 1 . 1 . 1 1 . . . . . 1 1 1 . 1
#> [34,] . . . . . . . . 1 1 . . . 1 1 1 . . 1 1 1 . 1 1 . . 1 1 1 1 1 1 1 .
as.matrix(g, "edgelist")
#> [,1] [,2]
#> [1,] 1 2
#> [2,] 1 3
#> [3,] 1 4
#> [4,] 1 5
#> [5,] 1 6
#> [6,] 1 7
#> [7,] 1 8
#> [8,] 1 9
#> [9,] 1 11
#> [10,] 1 12
#> [11,] 1 13
#> [12,] 1 14
#> [13,] 1 18
#> [14,] 1 20
#> [15,] 1 22
#> [16,] 1 32
#> [17,] 2 3
#> [18,] 2 4
#> [19,] 2 8
#> [20,] 2 14
#> [21,] 2 18
#> [22,] 2 20
#> [23,] 2 22
#> [24,] 2 31
#> [25,] 3 4
#> [26,] 3 8
#> [27,] 3 28
#> [28,] 3 29
#> [29,] 3 33
#> [30,] 3 10
#> [31,] 3 9
#> [32,] 3 14
#> [33,] 4 8
#> [34,] 4 13
#> [35,] 4 14
#> [36,] 5 7
#> [37,] 5 11
#> [38,] 6 7
#> [39,] 6 11
#> [40,] 6 17
#> [41,] 7 17
#> [42,] 9 31
#> [43,] 9 33
#> [44,] 9 34
#> [45,] 10 34
#> [46,] 14 34
#> [47,] 15 33
#> [48,] 15 34
#> [49,] 16 33
#> [50,] 16 34
#> [51,] 19 33
#> [52,] 19 34
#> [53,] 20 34
#> [54,] 21 33
#> [55,] 21 34
#> [56,] 23 33
#> [57,] 23 34
#> [58,] 24 26
#> [59,] 24 28
#> [60,] 24 33
#> [61,] 24 34
#> [62,] 24 30
#> [63,] 25 26
#> [64,] 25 28
#> [65,] 25 32
#> [66,] 26 32
#> [67,] 27 30
#> [68,] 27 34
#> [69,] 28 34
#> [70,] 29 32
#> [71,] 29 34
#> [72,] 30 33
#> [73,] 30 34
#> [74,] 31 33
#> [75,] 31 34
#> [76,] 32 33
#> [77,] 32 34
#> [78,] 33 34
# use edge attribute "weight"
E(g)$weight <- rep(1:10, length.out = ecount(g))
as.matrix(g, "adjacency", sparse = FALSE, attr = "weight")
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 0 1 2 3 4 5 6 7 8 0 9 10 1
#> [2,] 1 0 7 8 0 0 0 9 0 0 0 0 0
#> [3,] 2 7 0 5 0 0 0 6 1 10 0 0 0
#> [4,] 3 8 5 0 0 0 0 3 0 0 0 0 4
#> [5,] 4 0 0 0 0 0 6 0 0 0 7 0 0
#> [6,] 5 0 0 0 0 0 8 0 0 0 9 0 0
#> [7,] 6 0 0 0 6 8 0 0 0 0 0 0 0
#> [8,] 7 9 6 3 0 0 0 0 0 0 0 0 0
#> [9,] 8 0 1 0 0 0 0 0 0 0 0 0 0
#> [10,] 0 0 10 0 0 0 0 0 0 0 0 0 0
#> [11,] 9 0 0 0 7 9 0 0 0 0 0 0 0
#> [12,] 10 0 0 0 0 0 0 0 0 0 0 0 0
#> [13,] 1 0 0 4 0 0 0 0 0 0 0 0 0
#> [14,] 2 10 2 5 0 0 0 0 0 0 0 0 0
#> [15,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [16,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [17,] 0 0 0 0 0 10 1 0 0 0 0 0 0
#> [18,] 3 1 0 0 0 0 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [20,] 4 2 0 0 0 0 0 0 0 0 0 0 0
#> [21,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [22,] 5 3 0 0 0 0 0 0 0 0 0 0 0
#> [23,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [24,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [25,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [26,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [27,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [28,] 0 0 7 0 0 0 0 0 0 0 0 0 0
#> [29,] 0 0 8 0 0 0 0 0 0 0 0 0 0
#> [30,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [31,] 0 4 0 0 0 0 0 0 2 0 0 0 0
#> [32,] 6 0 0 0 0 0 0 0 0 0 0 0 0
#> [33,] 0 0 9 0 0 0 0 0 3 0 0 0 0
#> [34,] 0 0 0 0 0 0 0 0 4 5 0 0 0
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
#> [1,] 2 0 0 0 3 0 4 0 5 0 0 0
#> [2,] 10 0 0 0 1 0 2 0 3 0 0 0
#> [3,] 2 0 0 0 0 0 0 0 0 0 0 0
#> [4,] 5 0 0 0 0 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [6,] 0 0 0 10 0 0 0 0 0 0 0 0
#> [7,] 0 0 0 1 0 0 0 0 0 0 0 0
#> [8,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [9,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [10,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [11,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [12,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [13,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [14,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [15,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [16,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [17,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [18,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [20,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [21,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [22,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [23,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [24,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [25,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [26,] 0 0 0 0 0 0 0 0 0 0 8 3
#> [27,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [28,] 0 0 0 0 0 0 0 0 0 0 9 4
#> [29,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [30,] 0 0 0 0 0 0 0 0 0 0 2 0
#> [31,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [32,] 0 0 0 0 0 0 0 0 0 0 0 5
#> [33,] 0 7 9 0 0 1 0 4 0 6 10 0
#> [34,] 6 8 10 0 0 2 3 5 0 7 1 0
#> [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34]
#> [1,] 0 0 0 0 0 0 6 0 0
#> [2,] 0 0 0 0 0 4 0 0 0
#> [3,] 0 0 7 8 0 0 0 9 0
#> [4,] 0 0 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 0 0 0 0 0
#> [6,] 0 0 0 0 0 0 0 0 0
#> [7,] 0 0 0 0 0 0 0 0 0
#> [8,] 0 0 0 0 0 0 0 0 0
#> [9,] 0 0 0 0 0 2 0 3 4
#> [10,] 0 0 0 0 0 0 0 0 5
#> [11,] 0 0 0 0 0 0 0 0 0
#> [12,] 0 0 0 0 0 0 0 0 0
#> [13,] 0 0 0 0 0 0 0 0 0
#> [14,] 0 0 0 0 0 0 0 0 6
#> [15,] 0 0 0 0 0 0 0 7 8
#> [16,] 0 0 0 0 0 0 0 9 10
#> [17,] 0 0 0 0 0 0 0 0 0
#> [18,] 0 0 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 0 0 1 2
#> [20,] 0 0 0 0 0 0 0 0 3
#> [21,] 0 0 0 0 0 0 0 4 5
#> [22,] 0 0 0 0 0 0 0 0 0
#> [23,] 0 0 0 0 0 0 0 6 7
#> [24,] 8 0 9 0 2 0 0 10 1
#> [25,] 3 0 4 0 0 0 5 0 0
#> [26,] 0 0 0 0 0 0 6 0 0
#> [27,] 0 0 0 0 7 0 0 0 8
#> [28,] 0 0 0 0 0 0 0 0 9
#> [29,] 0 0 0 0 0 0 10 0 1
#> [30,] 0 7 0 0 0 0 0 2 3
#> [31,] 0 0 0 0 0 0 0 4 5
#> [32,] 6 0 0 10 0 0 0 6 7
#> [33,] 0 0 0 0 2 4 6 0 8
#> [34,] 0 8 9 1 3 5 7 8 0