R Under development (unstable) (2023-12-02 r85657 ucrt) -- "Unsuffered Consequences"
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> require("network")
Loading required package: network

'network' 1.18.2 (2023-12-04), part of the Statnet Project
* 'news(package="network")' for changes since last version
* 'citation("network")' for citation information
* 'https://statnet.org' for help, support, and other information

> set.seed(1702)
> 
> results = NULL
> 
> data("flo")
> data("emon")
> 
> net <- network.initialize(5)
> net
 Network attributes:
  vertices = 5 
  directed = TRUE 
  hyper = FALSE 
  loops = FALSE 
  multiple = FALSE 
  bipartite = FALSE 
  total edges= 0 
    missing edges= 0 
    non-missing edges= 0 

 Vertex attribute names: 
    vertex.names 

No edge attributes
> 
> nmat <- matrix(rbinom(25, 1, 0.5), nr = 5, nc = 5)
> net <- network(nmat, loops = TRUE)
> net
 Network attributes:
  vertices = 5 
  directed = TRUE 
  hyper = FALSE 
  loops = TRUE 
  multiple = FALSE 
  bipartite = FALSE 
  total edges= 9 
    missing edges= 0 
    non-missing edges= 9 

 Vertex attribute names: 
    vertex.names 

No edge attributes
> 
> summary(net)
Network attributes:
  vertices = 5
  directed = TRUE
  hyper = FALSE
  loops = TRUE
  multiple = FALSE
  bipartite = FALSE
 total edges = 9 
   missing edges = 0 
   non-missing edges = 9 
 density = 0.36 

Vertex attributes:
  vertex.names:
   character valued attribute
   5 valid vertex names

No edge attributes

Network adjacency matrix:
  1 2 3 4 5
1 1 0 1 0 1
2 1 0 0 1 0
3 1 0 1 1 0
4 0 0 1 0 0
5 0 0 0 0 0
> results[1] = all(nmat == net[,])
> 
> net <- as.network(nmat, loops = TRUE)
> results[2] = all(nmat == net[,])
> 
> nflo <- network(flo, directed = FALSE)
> nflo
 Network attributes:
  vertices = 16 
  directed = FALSE 
  hyper = FALSE 
  loops = FALSE 
  multiple = FALSE 
  bipartite = FALSE 
  total edges= 20 
    missing edges= 0 
    non-missing edges= 20 

 Vertex attribute names: 
    vertex.names 

No edge attributes
> 
> results[3] = all(nflo[9,] == c(1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1))
> results[4] = nflo[9,1] == 1
> results[5] = nflo[9,4] == 0
> results[6] = is.adjacent(nflo, 9, 1) == TRUE
> results[7] = is.adjacent(nflo, 9, 4) == FALSE
> 
> results[8] = network.size(nflo) ==  16
> results[9] = network.edgecount(nflo) == 20
> results[10] = network.density(nflo) == 1/6
> results[11] = has.loops(nflo) == FALSE
> results[12] = is.bipartite(nflo) == FALSE
> results[13] = is.directed(nflo) == FALSE
> results[14] = is.hyper(nflo) == FALSE
> results[15] = is.multiplex(nflo) == FALSE
> 
> as.sociomatrix(nflo)
             Acciaiuoli Albizzi Barbadori Bischeri Castellani Ginori Guadagni
Acciaiuoli            0       0         0        0          0      0        0
Albizzi               0       0         0        0          0      1        1
Barbadori             0       0         0        0          1      0        0
Bischeri              0       0         0        0          0      0        1
Castellani            0       0         1        0          0      0        0
Ginori                0       1         0        0          0      0        0
Guadagni              0       1         0        1          0      0        0
Lamberteschi          0       0         0        0          0      0        1
Medici                1       1         1        0          0      0        0
Pazzi                 0       0         0        0          0      0        0
Peruzzi               0       0         0        1          1      0        0
Pucci                 0       0         0        0          0      0        0
Ridolfi               0       0         0        0          0      0        0
Salviati              0       0         0        0          0      0        0
Strozzi               0       0         0        1          1      0        0
Tornabuoni            0       0         0        0          0      0        1
             Lamberteschi Medici Pazzi Peruzzi Pucci Ridolfi Salviati Strozzi
Acciaiuoli              0      1     0       0     0       0        0       0
Albizzi                 0      1     0       0     0       0        0       0
Barbadori               0      1     0       0     0       0        0       0
Bischeri                0      0     0       1     0       0        0       1
Castellani              0      0     0       1     0       0        0       1
Ginori                  0      0     0       0     0       0        0       0
Guadagni                1      0     0       0     0       0        0       0
Lamberteschi            0      0     0       0     0       0        0       0
Medici                  0      0     0       0     0       1        1       0
Pazzi                   0      0     0       0     0       0        1       0
Peruzzi                 0      0     0       0     0       0        0       1
Pucci                   0      0     0       0     0       0        0       0
Ridolfi                 0      1     0       0     0       0        0       1
Salviati                0      1     1       0     0       0        0       0
Strozzi                 0      0     0       1     0       1        0       0
Tornabuoni              0      1     0       0     0       1        0       0
             Tornabuoni
Acciaiuoli            0
Albizzi               0
Barbadori             0
Bischeri              0
Castellani            0
Ginori                0
Guadagni              1
Lamberteschi          0
Medici                1
Pazzi                 0
Peruzzi               0
Pucci                 0
Ridolfi               1
Salviati              0
Strozzi               0
Tornabuoni            0
> 
> results[16] = all(nflo[,] == as.sociomatrix(nflo))
> results[17] = all(as.matrix(nflo) == as.sociomatrix(nflo))
> as.matrix(nflo,matrix.type = "edgelist")
      [,1] [,2]
 [1,]    9    1
 [2,]    6    2
 [3,]    7    2
 [4,]    9    2
 [5,]    5    3
 [6,]    9    3
 [7,]    7    4
 [8,]   11    4
 [9,]   15    4
[10,]   11    5
[11,]   15    5
[12,]    8    7
[13,]   16    7
[14,]   13    9
[15,]   14    9
[16,]   16    9
[17,]   14   10
[18,]   15   11
[19,]   15   13
[20,]   16   13
attr(,"n")
[1] 16
attr(,"vnames")
 [1] "Acciaiuoli"   "Albizzi"      "Barbadori"    "Bischeri"     "Castellani"  
 [6] "Ginori"       "Guadagni"     "Lamberteschi" "Medici"       "Pazzi"       
[11] "Peruzzi"      "Pucci"        "Ridolfi"      "Salviati"     "Strozzi"     
[16] "Tornabuoni"  
> 
> net <- network.initialize(5, loops = TRUE)
> net[nmat>0] <- 1
> results[18] = all(nmat == net[,])
> 
> net[,] <- 0
> net[,] <- nmat
> results[19] = all(nmat == net[,])
> 
> net[,] <- 0
> for(i in 1:5)
+   for(j in 1:5)
+     if(nmat[i,j])
+       net[i,j] <- 1
> results[20] = all(nmat == net[,])
> 
> net[,] <- 0
> add.edges(net, row(nmat)[nmat>0], col(nmat)[nmat>0])
> results[21] = all(nmat == net[,])
> 
> net[,] <- as.numeric(nmat[,])
> results[22] = all(nmat == net[,])
> 
> net <- network.initialize(5)
> add.edge(net, 2, 3)
> net[,]
  1 2 3 4 5
1 0 0 0 0 0
2 0 0 1 0 0
3 0 0 0 0 0
4 0 0 0 0 0
5 0 0 0 0 0
> results[23] = net[2,3] == 1
> 
> add.edges(net, c(3, 5), c(4, 4))
> net[,]
  1 2 3 4 5
1 0 0 0 0 0
2 0 0 1 0 0
3 0 0 0 1 0
4 0 0 0 0 0
5 0 0 0 1 0
> results[24] = (net[3,4] == 1 && net[5,4] == 1)
> 
> net[,2] <- 1
> net[,]
  1 2 3 4 5
1 0 1 0 0 0
2 0 0 1 0 0
3 0 1 0 1 0
4 0 1 0 0 0
5 0 1 0 1 0
> results[25] = net[2,2] == 0
> 
> delete.vertices(net, 4)
> results[26] = all(net[,] == matrix(c(0,1,0,0,0,0,1,0,0,1,0,0,0,1,0,0), byrow=T, nrow=4))
> 
> add.vertices(net, 2)
> net[,]
     1 2 3 5 <NA> <NA>
1    0 1 0 0    0    0
2    0 0 1 0    0    0
3    0 1 0 0    0    0
5    0 1 0 0    0    0
<NA> 0 0 0 0    0    0
<NA> 0 0 0 0    0    0
> 
> get.edges(net, 1)
[[1]]
[[1]]$inl
[1] 2

[[1]]$outl
[1] 1

[[1]]$atl
[[1]]$atl$na
[1] FALSE



> get.edges(net, 2, neighborhood = "in")
[[1]]
[[1]]$inl
[1] 2

[[1]]$outl
[1] 4

[[1]]$atl
[[1]]$atl$na
[1] FALSE



[[2]]
[[2]]$inl
[1] 2

[[2]]$outl
[1] 3

[[2]]$atl
[[2]]$atl$na
[1] FALSE



[[3]]
[[3]]$inl
[1] 2

[[3]]$outl
[1] 1

[[3]]$atl
[[3]]$atl$na
[1] FALSE



> get.edges(net, 1, alter = 2)
[[1]]
[[1]]$inl
[1] 2

[[1]]$outl
[1] 1

[[1]]$atl
[[1]]$atl$na
[1] FALSE



> 
> results[27] = get.edgeIDs(net, 1) == 4
> results[28] = all(get.edgeIDs(net, 2, neighborhood = "in") == c(7, 5, 4))
> results[29] = get.edgeIDs(net, 1, alter = 2) == 4
> 
> results[30] = get.neighborhood(net, 1) == 2
> results[31] = all(get.neighborhood(net, 2, type = "in") == c(4, 3, 1))
> 
> net[2,3] <- 0
> results[32] = net[2,3] == 0
> 
> delete.edges(net, get.edgeIDs(net, 2, neighborhood = "in"))
> results[33] = all(net[,] == matrix(0, 6,6))
> 
> net <- network.initialize(5)
> set.network.attribute(net, "boo", 1:10)
> net %n% "hoo" <- letters[1:7]
> 
> results[34] = 'boo' %in% list.network.attributes(net)
> results[35] = 'hoo' %in% list.network.attributes(net)
> 
> results[36] = all(get.network.attribute(net, "boo") == c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
> results[37] = all(net %n% "hoo" == c("a", "b", "c", "d", "e", "f", "g"))
> 
> delete.network.attribute(net, "boo")
> results[38] = 'boo' %in% list.network.attributes(net) == FALSE
> 
> set.vertex.attribute(net, "boo", 1:5)
> net %v% "hoo" <- letters[1:5]
> results[39] = 'boo' %in% list.vertex.attributes(net)
> results[40] = 'hoo' %in% list.vertex.attributes(net)
> 
> results[41] = all(get.vertex.attribute(net, "boo") == 1:5)
> results[42] = all(net %v% "hoo" == letters[1:5])
> delete.vertex.attribute(net, "boo")
> results[43] = 'boo' %in% list.vertex.attributes(net) == FALSE
> 
> net <- network(nmat)
> set.edge.attribute(net, "boo", sum(nmat):1)
> set.edge.value(net, "hoo", matrix(1:25, 5, 5))
> net %e% "woo" <- matrix(rnorm(25), 5, 5)
> net[,, names.eval = "zoo"] <- nmat * 6
> results[44] = 'boo' %in% list.edge.attributes(net)
> results[45] = 'hoo' %in% list.edge.attributes(net)
> 
> results[46] = all(get.edge.attribute(get.edges(net, 1), "boo") == c(3,7))
> results[47] = all(get.edge.value(net, "hoo") == c(2, 3, 11, 14, 17, 18, 21))
> net %e% "woo"
[1]  0.8984226  0.4793125  3.7056453  0.7033602 -0.6100306 -0.4825138 -1.2331196
> as.sociomatrix(net, "zoo")
  1 2 3 4 5
1 0 0 6 0 6
2 6 0 0 6 0
3 6 0 0 6 0
4 0 0 6 0 0
5 0 0 0 0 0
> delete.edge.attribute(net, "boo")
> results[48] = 'boo' %in% list.edge.attributes(net) == FALSE
> 
> MtSHloc <- emon$MtStHelens %v% "Location"
> MtSHimat <- cbind(MtSHloc %in% c("L", "B"), MtSHloc %in% c("NL", "B"))
> MtSHbyloc <- network(MtSHimat, matrix = "incidence", hyper = TRUE,
+                         directed = FALSE, loops = TRUE)
> MtSHbyloc %v% "vertex.names" <- emon$MtStHelens %v% "vertex.names"
> MtSHbyloc
 Network attributes:
  vertices = 27 
  directed = FALSE 
  hyper = TRUE 
  loops = TRUE 
  multiple = FALSE 
  bipartite = FALSE 
  total edges= 2 
    missing edges= 0 
    non-missing edges= 2 

 Vertex attribute names: 
    vertex.names 

No edge attributes
> 
> plot(nflo, displaylabels = TRUE, boxed.labels = FALSE)
> plot(nflo, displaylabels = TRUE, mode = "circle")
> plot(emon$MtSi)
> 
> if (!all(results)) {
+   stop(paste('The following tests in vignette.R failed:', which(results==FALSE)))
+ }
> 
> 
> proc.time()
   user  system elapsed 
   0.71    0.17    0.87