make_brainGraphList error message: "'x' must be an array of at least two dimensions"

[Anthony Juliano]

Good afternoon everyone,

I am new to both R and brainGraph, so I apologize if the answer to the error message is super obvious.

I am trying to extract subject-level graphs using the Brainnetome atlas. All of my scripts are being run on an HPC using SLURM. 

Because this is a large dataset, I am only running one threshold per script (i.e. thresholds <- rev(seq(0.16, 0.16, 0.01))) in the call to make_brainGraphList (for both time and RAM constraints) and then merging the RDS outputs together after.

I am only getting this error for subject-level graphs (i.e. not getting it when generating the g.group graphs) and all of the subjects, files, etc. are identical that feed into the g and g.group calls (i.e. command on pg. 46 of the brainGraph_UserGuide for 3.0.0).

The error message that I am getting for every threshold for subject-level graphs is:

> g <- g.group <- vector('list', length(thresholds))
> for (j in seq_along(thresholds)) {
    g[[j]] <- make_brainGraphList(A.norm.sub[[j]], atlas, modality=modality,
        weighting='pearson', threshold=thresholds[j],
        weighted=TRUE, gnames=covars$Study.ID)
}
[1] "Start time: 2023-03-24 14:48:59"
  |======================================================================| 100%Error in { :
  task 2 failed - "'x' must be an array of at least two dimensions"

> traceback()
5: stop(simpleError(msg, call = expr))
4: e$fun(obj, substitute(ex), parent.frame(), e$data)
3: foreach(i = seq_len(kNumGraphs)) %dopar% {
       res <- loopfun(x[, , i], atlas, type, level, set.attrs, modality,
           weighting, threshold[i], name = gnames[i], Group = grpNames[i],
           subnet = subnet, mode = mode, diag = diag, weighted = weighted,
           use.parallel = FALSE, ...)
   }
2: make_brainGraphList.array(A.norm.sub[[j]], atlas, modality = modality,
       weighting = "pearson", threshold = thresholds[j], weighted = TRUE,
       gnames = covars$Study.ID)
1: make_brainGraphList(A.norm.sub[[j]], atlas, modality = modality,
       weighting = "pearson", threshold = thresholds[j], weighted = TRUE,
       gnames = covars$Study.ID)

> warnings()
>

 

Again, this error is not generated in the group graphs (which I ran in separate scripts), only when generating the subject-level graphs, so I am fairly confident that my matrices, covars, etc. were set up properly.

I also tried this with R version 3.6.3 (2020-02-29) just in case there were issues between R version 3 and R version 4, but it was the same error.

I also tried adding in the "grpNames=covars$Group" argument, but that also generated the same error (i.e. 'x' must be an array of at least two dimensions).

I should also mention that I ran it with the "set.attrs=FALSE" argument and it did run without generating any error, but then once I got to the the next series of commands (after the merge), it created several issues (i.e. these commands...

dt.V <- rbindlist(lapply(g, vertex_attr_dt))
dt.G <- rbindlist(lapply(g, graph_attr_dt)))

Additional information is below. Hopefully this gives enough information to help figure out what is going on.

Please let me know and thank you!

Anthony

Call to SLURM interactive job: srun -p short -N 1 -n 2 --mem-per-cpu=5G -t 180 --pty bash

> sessionInfo()
R version 4.2.2 (2022-10-31)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux Server 7.9 (Maipo)

Matrix products: default
BLAS/LAPACK: /PATH_TO_ANACONDA/anaconda3/envs/MyNewEnvironment/lib/libopenblasp-r0.3.21.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8  
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C      

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods  
[8] base    

other attached packages:
 [1] doMC_1.3.8        iterators_1.0.14  foreach_1.5.2     expm_0.999-7    
 [5] Matrix_1.5-3      ade4_1.7-22       Hmisc_5.0-1       boot_1.3-28.1    
 [9] ggpubr_0.6.0      data.table_1.14.8 ggplot2_3.4.1     tidyr_1.3.0      
[13] dplyr_1.1.0       brainGraph_3.0.2  igraph_1.4.1    

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.10       lattice_0.20-45   digest_0.6.31     utf8_1.2.3      
 [5] R6_2.5.1          backports_1.4.1   evaluate_0.20     pillar_1.8.1    
 [9] rlang_1.1.0       rstudioapi_0.14   car_3.1-1         rpart_4.1.19    
[13] checkmate_2.1.0   rmarkdown_2.20    stringr_1.5.0     foreign_0.8-84  
[17] htmlwidgets_1.6.1 munsell_0.5.0     broom_1.0.4       compiler_4.2.2  
[21] xfun_0.37         pkgconfig_2.0.3   base64enc_0.1-3   htmltools_0.5.4  
[25] nnet_7.3-18       tidyselect_1.2.0  tibble_3.2.0      gridExtra_2.3    
[29] htmlTable_2.4.1   codetools_0.2-19  fansi_1.0.4       permute_0.9-7    
[33] withr_2.5.0       MASS_7.3-58.3     grid_4.2.2        gtable_0.3.1    
[37] lifecycle_1.0.3   magrittr_2.0.3    scales_1.2.1      cli_3.6.0        
[41] stringi_1.7.12    carData_3.0-5     ggsignif_0.6.4    doParallel_1.0.17
[45] generics_0.1.3    vctrs_0.5.2       Formula_1.2-5     tools_4.2.2      
[49] glue_1.6.2        purrr_1.0.1       abind_1.4-5       fastmap_1.1.1    
[53] colorspace_2.1-0  cluster_2.1.4     rstatix_0.7.2     knitr_1.42      


> detectCores()
[1] 16

 

[Chris Watson]

Are you getting the same error for high thresholds? Sometimes that error occurs on more sparse graphs. Anyway, I'd need some data and your code to try to debug/recreate the issue.

Chris

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