"Object NA" error when control for clustering

[Gershon Spitz]

Dear Chris,

When generating random graphs controlling for clustering I have the following error:

Error in { : task 1 failed - "object 'NA' not found"

Code is:

kNumRandClust <- 1e2 # Create 100 graphs per group/density combination
bgl.rand <- g.rand <- small.clust.dt <- vector('list', length(g))
for (i in seq_along(g)) {
g.rand[[i]] <- vector('list', length=nobs(g[[i]]))
for (j in seq_len(nobs(g[[i]]))) {
g.rand[[i]][[j]] <- sim.rand.graph.par(g[[i]][j], level=g[[i]]$level,
kNumRandClust, clustering=T,
name=g[[i]][j]$name)
}
bgl.rand[[i]] <- as_brainGraphList(g.rand[[i]], type='random', level=g[[i]]$level)
small.clust.dt[[i]] <- small.world(g[[i]], bgl.rand[[i]])
}
small.clust.dt <- rbindlist(small.clust.dt)

My g object is attached. I am using a custom atlas (Schaefer).

Any help would be greatly appreciated.

Best wishes,

Gershon.

 g.rds

--

GERSHON SPITZ
PhD, BA
Research Fellow, National Health and Medical Research Council

Research Fellow, Monash-Epworth Rehabilitation Research Centre

Deputy Program Lead, Brain Injury and Rehabilitation

Monash University
Turner Institute for Brain and Mental Health

School of Psychological Sciences
18 Innovation Walk
Clayton, VIC 3800

Australia

T:+61 3 9902 0238
E: gersho...@monash.edu

monash.edu/turner-institute/home   

[Chris Watson]

That is related to the atlas. The fastest solution would be to add the following line (the first one) in the "sim.rand.graph.par" function:

tmp$atlas <- g$atlas

tmp <- make_brainGraph(tmp, type='random', level=level, set.attrs=TRUE, ...)

It is in the "isTRUE(clustering)" branch in that function.

You may have to also export the atlas itself when setting up the cluster by adding

.export='Schaefer2018_400Parcels_7Networks'

to the "foreach" function call. Unfortunately, I am still not sure this will work and do not know of the best workaround yet.

Just be aware that depending on your computer's capabilities, this will probably take a very long time.

Chris

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[Gershon Spitz]

Hi Chris,

Thank you for the reply.

I amended the function but still received the same error message.

I amended the function in the following way:

sim.rand.graph.par_v2 <- function (g, level = c("subject", "group"), N = 100L, clustering = FALSE,
  rewire.iters = max(10 * ecount(g), 10000L), cl = g$transitivity,
  max.iters = 100L, ...)
{
  stopifnot(is_igraph(g))
  level <- match.arg(level)
  if (!getDoParRegistered()) {
    clust <- makeCluster(getOption("bg.ncpus"))
    registerDoParallel(clust)
  }
  if (isTRUE(clustering)) {
    r <- foreach(i = seq_len(N), .packages = c("igraph",
      "brainGraph"), .export='Schaefer2018_400Parcels_7Networks') %dopar% {
      tmp <- sim.rand.graph.clust(g, rewire.iters, cl,
        max.iters)
      tmp$atlas <- g$atlas
      tmp <- make_brainGraph(tmp, type = "random", level = level,
        set.attrs = TRUE, ...)
      tmp
    }
  }
  else {
    if (is_connected(g)) {
      V(g)$degree <- degree(g)
      r <- foreach(i = seq_len(N)) %dopar% {
        tmp <- sample_degseq(V(g)$degree, method = "vl")
        tmp$Group <- g$Group
        tmp$name <- g$name
        tmp$threshold <- g$threshold
        tmp$density <- graph.density(tmp)
        tmp <- make_brainGraph(tmp, type = "random",
          level = level, set.attrs = TRUE, ...)
        tmp
      }
    }
    else {
      r <- foreach(i = seq_len(N)) %dopar% {
        tmp <- rewire(g, keeping_degseq(loops = FALSE,
          rewire.iters))
        tmp <- make_brainGraph(tmp, type = "random",
          level = level, set.attrs = TRUE, ...)
        tmp
      }
    }
  }
}

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