Last updated on 2024-10-31 10:50:20 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| ergmgp | 13 | ||
| network | 1 | 3 | 9 |
| relevent | 10 | 3 | |
| sna | 13 | ||
| yacca | 13 |
Current CRAN status: OK: 13
Current CRAN status: ERROR: 1, NOTE: 3, OK: 9
Version: 1.18.2
Check: Rd cross-references
Result: NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
as.edgelist.Rd: tibble
as.matrix.network.Rd: tibble
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-windows-x86_64
Version: 1.18.2
Check: examples
Result: ERROR
Running examples in ‘network-Ex.R’ failed
The error most likely occurred in:
> ### Name: edgeset.constructors
> ### Title: Edgeset Constructors for Network Objects
> ### Aliases: edgeset.constructors network.bipartite network.adjacency
> ### network.edgelist network.incidence
> ### Keywords: classes graphs
>
> ### ** Examples
>
> #Create an arbitrary adjacency matrix
> m<-matrix(rbinom(25,1,0.5),5,5)
> diag(m)<-0
>
> g<-network.initialize(5) #Initialize the network
> network.adjacency(m,g) #Import the edge data
>
> #Do the same thing, using replacement operators
> g<-network.initialize(5)
> g[,]<-m
>
> # load edges from a data.frame via network.edgelist
> edata <-data.frame(
+ tails=c(1,2,3),
+ heads=c(2,3,1),
+ love=c('yes','no','maybe'),
+ hate=c(3,-5,2),
+ stringsAsFactors=FALSE
+ )
>
> g<-network.edgelist(edata,network.initialize(4),ignore.eval=FALSE)
> as.sociomatrix(g,attrname='hate')
1 2 3 4
1 0 3 0 0
2 0 0 -5 0
3 2 0 0 0
4 0 0 0 0
> g%e%'love'
[1] "yes" "no" "maybe"
>
> # load edges from an incidence matrix
> inci<-matrix(c(1,1,0,0, 0,1,1,0, 1,0,1,0),ncol=3,byrow=FALSE)
> inci
[,1] [,2] [,3]
[1,] 1 0 1
[2,] 1 1 0
[3,] 0 1 1
[4,] 0 0 0
> g<-network.incidence(inci,network.initialize(4,directed=FALSE))
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: add.edge.network(g, tail, head, names.eval = en, vals.eval = ev, edge.check = edge.check)
2: add.edge(g, tail, head, names.eval = en, vals.eval = ev, edge.check = edge.check)
3: network.incidence(inci, network.initialize(4, directed = FALSE))
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.18.2
Check: tests
Result: ERROR
Running ‘general.tests.R’
Running ‘general.tests2.R’
Running ‘list.attribute.tests.R’
Running ‘network.access.test.R’
Running ‘network.battery.R’
Running ‘pathological.tests.R’
Running ‘plotflo.R’
Running ‘speedTests.R’
Running ‘testthat.R’ [4s/388s]
Running ‘vignette.R’ [2s/302s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(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
>
> test_check("network")
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: add.edge.network(g, tail, head, names.eval = en, vals.eval = ev, edge.check = edge.check)
2: add.edge(g, tail, head, names.eval = en, vals.eval = ev, edge.check = edge.check)
3: network.incidence(x, g, ignore.eval, names.eval, na.rm, edge.check)
4: as.network.matrix(x, directed = directed, hyper = hyper, loops = loops, multiple = multiple, bipartite = bipartite, ...)
5: as.network(x, directed = directed, hyper = hyper, loops = loops, multiple = multiple, bipartite = bipartite, ...)
6: network(MtSHimat, matrix.type = "incidence", hyper = TRUE, directed = FALSE, loops = TRUE)
7: eval(code, test_env)
8: eval(code, test_env)
9: withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error)
10: doTryCatch(return(expr), name, parentenv, handler)
11: tryCatchOne(expr, names, parentenv, handlers[[1L]])
12: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
13: doTryCatch(return(expr), name, parentenv, handler)
14: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]])
15: tryCatchList(expr, classes, parentenv, handlers)
16: tryCatch(withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error), error = handle_fatal, skip = function(e) { })
17: test_code(desc, code, env = parent.frame(), default_reporter = local_interactive_reporter())
18: test_that("hyper-edges work", { hyper_edge_df <- structure(list(.tail = list(1:4, 3:5, 4:7, 6:10), .head = list(1:4, 3:5, 4:7, 6:10), value = as.double(5:8)), row.names = 1:4, class = "data.frame") hyper_target_net <- network.initialize(10, directed = FALSE, hyper = TRUE, loops = TRUE) hyper_target_net <- add.edge(hyper_target_net, 1:4, 1:4, "value", list(5)) hyper_target_net <- add.edge(hyper_target_net, 3:5, 3:5, "value", list(6)) hyper_target_net <- add.edge(hyper_target_net, 4:7, 4:7, "value", list(7)) hyper_target_net <- add.edge(hyper_target_net, 6:10, 6:10, "value", list(8)) expect_identical(as.network(hyper_edge_df, directed = FALSE, hyper = TRUE, loops = TRUE), hyper_target_net) expect_identical(hyper_edge_df, as.data.frame(hyper_target_net)) MtSHbyloc_edge_df <- structure(list(.tail = list(as.integer(c(1, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27)), as.integer(c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 26, 27))), .head = list(as.integer(c(1, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27)), as.integer(c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 26, 27)))), row.names = 1:2, class = "data.frame") MtSHbyloc_vertex_df <- data.frame(vertex.names = 1:27) data("emon") MtSHloc <- emon$MtStHelens %v% "Location" MtSHimat <- cbind(MtSHloc %in% c("L", "B"), MtSHloc %in% c("NL", "B")) MtSHbyloc <- network(MtSHimat, matrix.type = "incidence", hyper = TRUE, directed = FALSE, loops = TRUE) expect_identical(as.network(MtSHbyloc_edge_df, directed = FALSE, vertices = MtSHbyloc_vertex_df, loops = TRUE, hyper = TRUE), MtSHbyloc) expect_identical(MtSHbyloc_edge_df, as.data.frame(MtSHbyloc)) expect_identical(MtSHbyloc_vertex_df, as.data.frame(MtSHbyloc, unit = "vertices")) delete.edges(MtSHbyloc, 2) expect_identical(`rownames<-`(MtSHbyloc_edge_df[-2, ], NULL), as.data.frame(MtSHbyloc)) delete.vertices(MtSHbyloc, 2) expect_identical(`rownames<-`(MtSHbyloc_vertex_df[-2, , drop = FALSE], NULL), as.data.frame(MtSHbyloc, unit = "vertices")) hyper_edges_with_NA <- data.frame(from = I(list(c(NA, "a", "b"))), to = I(list(c("c", "d")))) expect_error(as.network(hyper_edges_with_NA, hyper = TRUE), "`x`'s first two columns contain invalid values.") non_hyper_edges <- data.frame(from = 1:3, to = 4:6) expect_error(as.network(non_hyper_edges, hyper = TRUE), "If `hyper` is `TRUE`, the first two columns of `x` should be list columns.") incompat_type_hyper_edges <- data.frame(from = I(list(letters[1:5], 1:5)), to = I(list(letters[6:10], letters[11:15]))) expect_error(as.network(incompat_type_hyper_edges, hyper = T), "The values in the first two columns of `x` must be of the same type and cannot be `NULL`, `NA`, or recursive values.") loop_hyper_edges <- data.frame(from = I(list(c("a", "b"))), to = I(list(c("a", "b")))) expect_error(as.network(loop_hyper_edges, hyper = TRUE), "`loops` is `FALSE`, but `x` contains loops.")})
19: eval(code, test_env)
20: eval(code, test_env)
21: withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error)
22: doTryCatch(return(expr), name, parentenv, handler)
23: tryCatchOne(expr, names, parentenv, handlers[[1L]])
24: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
25: doTryCatch(return(expr), name, parentenv, handler)
26: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]])
27: tryCatchList(expr, classes, parentenv, handlers)
28: tryCatch(withCallingHandlers({ eval(code, test_env) if (!handled && !is.null(test)) { skip_empty() }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error), error = handle_fatal, skip = function(e) { })
29: test_code(test = NULL, code = exprs, env = env, default_reporter = StopReporter$new())
30: source_file(path, env = env(env), desc = desc, error_call = error_call)
31: FUN(X[[i]], ...)
32: lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call)
33: doTryCatch(return(expr), name, parentenv, handler)
34: tryCatchOne(expr, names, parentenv, handlers[[1L]])
35: tryCatchList(expr, classes, parentenv, handlers)
36: tryCatch(code, testthat_abort_reporter = function(cnd) { cat(conditionMessage(cnd), "\n") NULL})
37: with_reporter(reporters$multi, lapply(test_paths, test_one_file, env = env, desc = desc, error_call = error_call))
38: test_files_serial(test_dir = test_dir, test_package = test_package, test_paths = test_paths, load_helpers = load_helpers, reporter = reporter, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, desc = desc, load_package = load_package, error_call = error_call)
39: test_files(test_dir = path, test_paths = test_paths, test_package = package, reporter = reporter, load_helpers = load_helpers, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, load_package = load_package, parallel = parallel)
40: test_dir("testthat", package = package, reporter = reporter, ..., load_package = "installed")
41: test_check("network")
An irrecoverable exception occurred. R is aborting now ...
Running the tests in ‘tests/vignette.R’ failed.
Complete output:
> 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)
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: add.edge.network(g, tail, head, names.eval = en, vals.eval = ev, edge.check = edge.check)
2: add.edge(g, tail, head, names.eval = en, vals.eval = ev, edge.check = edge.check)
3: network.incidence(x, g, ignore.eval, names.eval, na.rm, edge.check)
4: as.network.matrix(x, directed = directed, hyper = hyper, loops = loops, multiple = multiple, bipartite = bipartite, ...)
5: as.network(x, directed = directed, hyper = hyper, loops = loops, multiple = multiple, bipartite = bipartite, ...)
6: network(MtSHimat, matrix = "incidence", hyper = TRUE, directed = FALSE, loops = TRUE)
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.18.2
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building ‘networkVignette.Rnw’ using Sweave
‘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
*** caught segfault ***
address 0x1, cause 'memory not mapped'
Traceback:
1: add.edge.network(g, tail, head, names.eval = en, vals.eval = ev, edge.check = edge.check)
2: add.edge(g, tail, head, names.eval = en, vals.eval = ev, edge.check = edge.check)
3: network.incidence(x, g, ignore.eval, names.eval, na.rm, edge.check)
4: as.network.matrix(x, directed = directed, hyper = hyper, loops = loops, multiple = multiple, bipartite = bipartite, ...)
5: as.network(x, directed = directed, hyper = hyper, loops = loops, multiple = multiple, bipartite = bipartite, ...)
6: network(MtSHimat, matrix = "incidence", hyper = TRUE, directed = FALSE, loops = TRUE)
7: eval(expr, .GlobalEnv)
8: eval(expr, .GlobalEnv)
9: withVisible(eval(expr, .GlobalEnv))
10: doTryCatch(return(expr), name, parentenv, handler)
11: tryCatchOne(expr, names, parentenv, handlers[[1L]])
12: tryCatchList(expr, classes, parentenv, handlers)
13: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call, nlines = 1L) prefix <- paste("Error in", dcall, ": ") LONG <- 75L sm <- strsplit(conditionMessage(e), "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && isTRUE(getOption("show.error.messages"))) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})
14: try(withVisible(eval(expr, .GlobalEnv)), silent = TRUE)
15: evalFunc(ce, options)
16: tryCatchList(expr, classes, parentenv, handlers)
17: tryCatch(evalFunc(ce, options), finally = { cat("\n") sink()})
18: driver$runcode(drobj, chunk, chunkopts)
19: utils::Sweave(...)
20: engine$weave(file, quiet = quiet, encoding = enc)
21: doTryCatch(return(expr), name, parentenv, handler)
22: tryCatchOne(expr, names, parentenv, handlers[[1L]])
23: tryCatchList(expr, classes, parentenv, handlers)
24: tryCatch({ engine$weave(file, quiet = quiet, encoding = enc) setwd(startdir) output <- find_vignette_product(name, by = "weave", engine = engine) if (!have.makefile && vignette_is_tex(output)) { texi2pdf(file = output, clean = FALSE, quiet = quiet) output <- find_vignette_product(name, by = "texi2pdf", engine = engine) } outputs <- c(outputs, output)}, error = function(e) { thisOK <<- FALSE fails <<- c(fails, file) message(gettextf("Error: processing vignette '%s' failed with diagnostics:\n%s", file, conditionMessage(e)))})
25: tools::buildVignettes(dir = "/data/gannet/ripley/R/packages/tests-devel/network.Rcheck/vign_test/network", skip = TRUE, ser_elibs = "/tmp/RtmpeYLmjv/file24a8c3e0ee465.rds")
An irrecoverable exception occurred. R is aborting now ...
Flavor: r-devel-linux-x86_64-fedora-gcc
Current CRAN status: NOTE: 10, OK: 3
Version: 1.2-1
Check: Rd files
Result: NOTE
checkRd: (-1) rem.dyad.Rd:121: Lost braces; missing escapes or markup?
121 | \item Single or multiple covariates, time varying: For \code{CovSnd}, \code{CovRec}, or \code{CovInt}, an \code{m} by \code{p} by {n} array whose respective dimensions index time (i.e., event number), covariate, and actor. For \code{CovEvent}, a \code{m} by \code{p} by \code{n} by \code{n} array, whose dimensions are analogous to the previous case.
| ^
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64
Current CRAN status: OK: 13
Current CRAN status: OK: 13