LouvainKRange run error

[chapmanchao]

Running this line of code:
pisces.obj <- LouvainKRange(pisces.obj, kmax = 100)

Error in dimnames(x) <- dn : length of 'dimnames' [2] not equal to array extent

The code of LouvainKRange and LouvainClust are following：

LouvainClust <- function(dat.mat, k = 100) {
  require(MUDAN)
  set.seed(1)
  res <- MUDAN::getComMembership(t(dat.mat), k = k, method = igraph::cluster_infomap, verbose = FALSE)
  #as(adj.mat, "sparseMatrix")
  #res <- MUDAN::getComMembership(as(t(dat.mat),"sparseMatrix"), k = k, method = igraph::cluster_infomap, verbose = FALSE)
  return(res)
}

LouvainKRange <- function(data.obj, kmin = 5, kmax = 50, kstep = 5) {
  require(igraph, quietly = TRUE)
  # check if seurat object
  if (class(data.obj)[1] == "Seurat") {
   dist.mat <- data.obj@assays[[data.obj@active.assay]]@misc$dist.mat
  } else {
    dist.mat <- data.obj
  }
  # create lists
  cluster.list <- list()
  sil.list <- list()
  # setup iteration
  k <- kmin
  while (k <= kmax) {
    print(paste("Clustering with k = ", k, "...", sep = ''))
    # generate clustering and silhouette score
    clust.vec <- LouvainClust(dist.mat, k)
    sil.score <- cluster::silhouette(clust.vec, dist.mat)
    # add to list
    k.ind <- paste('k', k, sep = '.')
    cluster.list[[k.ind]] <- clust.vec
    sil.list[[k.ind]] <- mean(sil.score[,3])
    # iterate
    k <- k + kstep
  }
  # identify optimal cluster
  opt.clust <- cluster.list[[which.max(sil.list)]]
  # add to data.object
  if (class(data.obj)[1] == "Seurat") {
    data.obj@assays[[data.obj@active.assay]]@misc[['pisces.cluster']] <- opt.clust
    data.obj@assays[[data.obj@active.assay]]@misc[['clustering.obj']] <- list('clusterings' = cluster.list, 'sils' = sil.list)
    return(data.obj)
  } else {
    return(list('pisces.cluster' = opt.clust, 'clustering.obj' = list('clusterings' = cluster.list, 'sils' = sil.list)))
  }
}