Error invalid class object

Also, it’s most likely you haven’t defined a global variable named no_railgun_inaccuracy and assigned it the checkbox object, so i suggest getting the checkbox from the form it is on
E.g myformname.no_railgun_inaccuracy
_________________

780)?780:this.scrollWidth); max-width:780px; height: expression((parseInt(this.scrollHeight)>300)?300:this.scrollHeight); overflow: hidden; max-height:300px;»> Do not ask me about online cheats. I don’t know any and wont help finding them.

Like my help? Join me on Patreon so i can keep helping

Источник

FindNeighbors() error: invalid class “Graph” object: superclass «Mnumeric» not defined.. #4436

Initially ran into this error on a small 1k pbmc dataset, but was able to reproduce it using the dataset given for the Guided Clustering Tutorial using the exact same Rmd file. IIRC, the error popped up when attempting to knit the document (however, when assembling my custom Rmd file, the code chunks ran perfectly fine). Since attempting to knit the document, the error has persisted — even after restarts of both RStudio and Ubuntu. Perhaps worth mentioning that I recently updated Ubuntu and did a fresh install of R, RStudio, perhaps I am missing a package but it is not obvious to me with my limited experience with Seurat.

Error in validObject(.Object) : invalid class “Graph” object: superclass «Mnumeric» not defined in the environment of the object’s class

The text was updated successfully, but these errors were encountered:

HI! Same issue appeared on my macOS Catalina 10.15.7. not recalling if I updated anything. Perhaps just restarted my MAC.

Computing nearest neighbor graph Computing SNN Error in validObject(.Object) : invalid class “Graph” object: superclass «Mnumeric» not defined in the environment of the object’s class

sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.7

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
[1] Signac_1.2.0 RColorBrewer_1.1-2 gtools_3.8.2 cowplot_1.1.1
[5] gridExtra_2.3 gplots_3.1.1 ggplot2_3.3.3 pheatmap_1.0.12
[9] SeuratObject_4.0.0 Seurat_4.0.1 dplyr_1.0.5

loaded via a namespace (and not attached):
[1] fastmatch_1.1-0 plyr_1.8.6 igraph_1.2.6
[4] lazyeval_0.2.2 splines_4.0.3 BiocParallel_1.24.1
[7] listenv_0.8.0 SnowballC_0.7.0 scattermore_0.7
[10] GenomeInfoDb_1.26.7 digest_0.6.27 htmltools_0.5.1.1
[13] fansi_0.4.2 magrittr_2.0.1 tensor_1.5
[16] cluster_2.1.2 ROCR_1.0-11 limma_3.46.0
[19] globals_0.14.0 Biostrings_2.58.0 matrixStats_0.58.0
[22] docopt_0.7.1 spatstat.sparse_2.0-0 colorspace_2.0-1
[25] ggrepel_0.9.1 sparsesvd_0.2 crayon_1.4.1
[28] RCurl_1.98-1.3 jsonlite_1.7.2 spatstat.data_2.1-0
[31] survival_3.2-11 zoo_1.8-9 ape_5.5
[34] glue_1.4.2 polyclip_1.10-0 gtable_0.3.0
[37] zlibbioc_1.36.0 XVector_0.30.0 leiden_0.3.7
[40] future.apply_1.7.0 BiocGenerics_0.36.1 abind_1.4-5
[43] scales_1.1.1 DBI_1.1.1 edgeR_3.32.1
[46] miniUI_0.1.1.1 Rcpp_1.0.6 viridisLite_0.4.0
[49] xtable_1.8-4 tidytree_0.3.3 reticulate_1.20
[52] spatstat.core_2.1-2 stats4_4.0.3 htmlwidgets_1.5.3
[55] httr_1.4.2 ellipsis_0.3.2 ica_1.0-2
[58] pkgconfig_2.0.3 farver_2.1.0 ggseqlogo_0.1
[61] uwot_0.1.10 deldir_0.2-10 locfit_1.5-9.4
[64] utf8_1.2.1 labeling_0.4.2 tidyselect_1.1.1
[67] rlang_0.4.11 reshape2_1.4.4 later_1.2.0
[70] munsell_0.5.0 tools_4.0.3 generics_0.1.0
[73] ggridges_0.5.3 stringr_1.4.0 fastmap_1.1.0
[76] goftest_1.2-2 ggtree_2.4.2 fitdistrplus_1.1-3
[79] caTools_1.18.2 purrr_0.3.4 RANN_2.6.1
[82] pbapply_1.4-3 future_1.21.0 nlme_3.1-152
[85] mime_0.10 slam_0.1-48 RcppRoll_0.3.0
[88] aplot_0.0.6 compiler_4.0.3 rstudioapi_0.13
[91] plotly_4.9.3 png_0.1-7 spatstat.utils_2.1-0
[94] treeio_1.14.4 tibble_3.1.1 tweenr_1.0.2
[97] stringi_1.5.3 lattice_0.20-44 Matrix_1.3-3
[100] vctrs_0.3.8 pillar_1.6.0 lifecycle_1.0.0
[103] BiocManager_1.30.12 spatstat.geom_2.1-0 lmtest_0.9-38
[106] RcppAnnoy_0.0.18 data.table_1.14.0 bitops_1.0-7
[109] irlba_2.3.3 httpuv_1.6.0 patchwork_1.1.1
[112] GenomicRanges_1.42.0 R6_2.5.0 promises_1.2.0.1
[115] lsa_0.73.2 KernSmooth_2.23-20 IRanges_2.24.1
[118] parallelly_1.25.0 codetools_0.2-18 MASS_7.3-54
[121] assertthat_0.2.1 withr_2.4.2 qlcMatrix_0.9.7
[124] sctransform_0.3.2 Rsamtools_2.6.0 S4Vectors_0.28.1
[127] GenomeInfoDbData_1.2.4 mgcv_1.8-35 parallel_4.0.3
[130] rpart_4.1-15 tidyr_1.1.3 rvcheck_0.1.8
[133] Rtsne_0.15 ggforce_0.3.3 shiny_1.6.0

Hi, I’m also encountering the same issue, exact same command and error message. I installed Seurat in a fresh conda environment around 8 hours ago, and it worked fine. I then installed Scater, and suddenly I’m getting this error message. Perhaps there’s specific dependency causing an issue?

R version 4.0.3 (2020-10-10)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

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

other attached packages:
[1] SeuratObject_4.0.0 Seurat_4.0.1

loaded via a namespace (and not attached):
[1] nlme_3.1-152 spatstat.sparse_2.0-0 matrixStats_0.58.0
[4] RcppAnnoy_0.0.18 RColorBrewer_1.1-2 httr_1.4.2
[7] repr_1.1.3 sctransform_0.3.2 tools_4.0.3
[10] utf8_1.2.1 R6_2.5.0 irlba_2.3.3
[13] rpart_4.1-15 KernSmooth_2.23-20 uwot_0.1.10
[16] mgcv_1.8-35 DBI_1.1.1 lazyeval_0.2.2
[19] colorspace_2.0-1 tidyselect_1.1.1 gridExtra_2.3
[22] compiler_4.0.3 plotly_4.9.3 scales_1.1.1
[25] spatstat.data_2.1-0 lmtest_0.9-38 ggridges_0.5.3
[28] pbapply_1.4-3 goftest_1.2-2 pbdZMQ_0.3-5
[31] stringr_1.4.0 digest_0.6.27 spatstat.utils_2.1-0
[34] base64enc_0.1-3 pkgconfig_2.0.3 htmltools_0.5.1.1
[37] parallelly_1.25.0 fastmap_1.1.0 htmlwidgets_1.5.3
[40] rlang_0.4.11 shiny_1.6.0 generics_0.1.0
[43] zoo_1.8-9 jsonlite_1.7.2 ica_1.0-2
[46] dplyr_1.0.5 magrittr_2.0.1 patchwork_1.1.1
[49] Matrix_1.3-3 Rcpp_1.0.6 IRkernel_1.1.1
[52] munsell_0.5.0 fansi_0.4.2 abind_1.4-5
[55] reticulate_1.20 lifecycle_1.0.0 stringi_1.5.3
[58] MASS_7.3-54 Rtsne_0.15 plyr_1.8.6
[61] grid_4.0.3 parallel_4.0.3 listenv_0.8.0
[64] promises_1.2.0.1 ggrepel_0.9.1 crayon_1.4.1
[67] deldir_0.2-10 miniUI_0.1.1.1 lattice_0.20-44
[70] IRdisplay_1.0 cowplot_1.1.1 splines_4.0.3
[73] tensor_1.5 pillar_1.6.0 igraph_1.2.6
[76] uuid_0.1-4 spatstat.geom_2.1-0 future.apply_1.7.0
[79] reshape2_1.4.4 codetools_0.2-18 leiden_0.3.7
[82] glue_1.4.2 evaluate_0.14 data.table_1.14.0
[85] png_0.1-7 vctrs_0.3.8 httpuv_1.6.0
[88] polyclip_1.10-0 spatstat.core_2.1-2 gtable_0.3.0
[91] RANN_2.6.1 purrr_0.3.4 tidyr_1.1.3
[94] scattermore_0.7 future_1.21.0 assertthat_0.2.1
[97] ggplot2_3.3.3 mime_0.10 xtable_1.8-4
[100] later_1.2.0 viridisLite_0.4.0 survival_3.2-11
[103] tibble_3.1.1 cluster_2.1.2 globals_0.14.0
[106] fitdistrplus_1.1-3 ellipsis_0.3.2 ROCR_1.0-11

I believe it’s a problem related to the latest version of the Matrix package (1.3-3). I updated my packages today and ran into the same error message. Searching the web, I found this issue associating a similar error with the Matrix package. Downgrading for version 1.3-2 solved the problem.

A modification related to ‘Mnumeric’ is mentioned in the description of the update (https://cloud.r-project.org/web/packages/Matrix/news.html):
«removed the nowhere used (and unexported but still active) class union «Mnumeric» which actually trickled into many base classes properties. Notably would it break validity of factor with a proposed change in validity checking, as factors were also «Mnumeric» but did not fulfill its validity method.»

Super detective work @ftencaten 😎

Very useful, thanks! And do not forget to restart your Rstudio. 😎

Источник

Error: invalid class»otu_table» object #1225

I ran this command — ps.ctrls

The text was updated successfully, but these errors were encountered:

I have figured this out. It worked after some trials

Hello,
I am experiencing the same issue. Can you provide some insight into what the problem was/what you changed?

I have to provide the correct variable in which I stored my OTU_table. So when I put the right variable in the above code, it ran successfully .

I have it working now also. Thank you so much for the help.

Hi
I am doing some microbiome analysis I am in the filtering step after the decontam and I got to this error that I can’t find any solution. Could you help me with that? After the following code, I get the error

filter for relative abundance

transform to relative abundance

pst 1e-5, TRUE)
Error in validObject(.Object) : invalid class “otu_table” object:
OTU abundance data must have non-zero dimensions.

I thought there was a problem in my pst but here is the info of it:
phyloseq-class experiment-level object
otu_table() OTU Table: [ 3377 taxa and 51 samples ]
sample_data() Sample Data: [ 51 samples by 3 sample variables ]
tax_table() Taxonomy Table: [ 3377 taxa by 6 taxonomic ranks ]

Any help would be very appreciatted.
Thank you

@aff30 This looks like an issue with the phyloseq package rather than the dada2 package, you might want to look at the phyloseq site.

I don’t know what is going on, but I’d start by taking a look at the logical vector that filter_taxa makes, to see if it sensible or if perhaps every taxa is being removed or something.

Источник

Invalid class dgCMatrix object #2

Trying to load a MAT file with objects of two classes — double & cell.

The variables shown in the image belong to the following classes:

• X , Y , Y2 — double (sparse matrices)
• all_sentiments — double (vector)
• all_genres — cell

Hi,

Initially ran into this error on a small 1k pbmc dataset, but was able to reproduce it using the dataset given for the Guided Clustering Tutorial using the exact same Rmd file. IIRC, the error popped up when attempting to knit the document (however, when assembling my custom Rmd file, the code chunks ran perfectly fine). Since attempting to knit the document, the error has persisted — even after restarts of both RStudio and Ubuntu. Perhaps worth mentioning that I recently updated Ubuntu and did a fresh install of R, RStudio, perhaps I am missing a package but it is not obvious to me with my limited experience with Seurat.

line 267:

pbmc <- FindNeighbors(pbmc, dims = 1:10) # <- problem line
pbmc <- FindClusters(pbmc, resolution = 0.5)

# Look at cluster IDs of the first 5 cells
head(Idents(pbmc), 5)

Error:

Error in validObject(.Object) : invalid class “Graph” object: superclass «Mnumeric» not defined in the environment of the object’s class

Traceback:

13. stop(msg, ": ", errors, domain = NA)
12. validObject(.Object)
11. .nextMethod(.Object = .Object, ... = ...)
10. callNextMethod()
9. initialize(value, ...)
8. initialize(value, ...)
7. new(Class = "Graph", i = c(0L, 6L, 102L, 203L, 292L, 421L, 451L, 511L, 547L, 618L, 651L, 767L, 963L, 978L, 1005L, 1043L, 1148L, 1156L, 1264L, 1337L, 1338L, 1385L, 1504L, 1554L, 1573L, 1620L, 1695L, 1851L, 1904L, 1991L, 2079L, 2136L, 2187L, 2296L, 2317L, ...
6. do.call(what = "new", args = object.list)
5. UpdateSlots(object = object)
4. `DefaultAssay<-.Graph`(object = `*tmp*`, value = assay)
3. `DefaultAssay<-`(object = `*tmp*`, value = assay)
2. FindNeighbors.Seurat(pbmc, dims = 1:10)
1. FindNeighbors(pbmc, dims = 1:10)

> sessionInfo()
R version 4.0.5 (2021-03-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.2 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=en_IE.UTF-8       LC_NUMERIC=C               LC_TIME=en_IE.UTF-8        LC_COLLATE=en_IE.UTF-8     LC_MONETARY=en_IE.UTF-8   
 [6] LC_MESSAGES=en_IE.UTF-8    LC_PAPER=en_IE.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_IE.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
[1] SeuratObject_4.0.0 dplyr_1.0.5        patchwork_1.1.1    Seurat_4.0.1      

loaded via a namespace (and not attached):
  [1] nlme_3.1-152          spatstat.sparse_2.0-0 matrixStats_0.58.0    RcppAnnoy_0.0.18      RColorBrewer_1.1-2    httr_1.4.2            sctransform_0.3.2    
  [8] tools_4.0.5           utf8_1.2.1            R6_2.5.0              irlba_2.3.3           rpart_4.1-15          KernSmooth_2.23-20    uwot_0.1.10          
 [15] mgcv_1.8-35           DBI_1.1.1             lazyeval_0.2.2        colorspace_2.0-1      withr_2.4.2           tidyselect_1.1.1      gridExtra_2.3        
 [22] compiler_4.0.5        cli_2.5.0             plotly_4.9.3          labeling_0.4.2        scales_1.1.1          spatstat.data_2.1-0   lmtest_0.9-38        
 [29] ggridges_0.5.3        pbapply_1.4-3         goftest_1.2-2         stringr_1.4.0         digest_0.6.27         spatstat.utils_2.1-0  rmarkdown_2.7        
 [36] pkgconfig_2.0.3       htmltools_0.5.1.1     parallelly_1.25.0     fastmap_1.1.0         htmlwidgets_1.5.3     rlang_0.4.11          rstudioapi_0.13      
 [43] shiny_1.6.0           farver_2.1.0          generics_0.1.0        zoo_1.8-9             jsonlite_1.7.2        ica_1.0-2             magrittr_2.0.1       
 [50] Matrix_1.3-3          Rcpp_1.0.6            munsell_0.5.0         fansi_0.4.2           abind_1.4-5           reticulate_1.20       lifecycle_1.0.0      
 [57] stringi_1.5.3         yaml_2.2.1            MASS_7.3-54           Rtsne_0.15            plyr_1.8.6            grid_4.0.5            parallel_4.0.5       
 [64] listenv_0.8.0         promises_1.2.0.1      ggrepel_0.9.1         crayon_1.4.1          deldir_0.2-10         miniUI_0.1.1.1        lattice_0.20-44      
 [71] cowplot_1.1.1         splines_4.0.5         tensor_1.5            knitr_1.33            pillar_1.6.0          igraph_1.2.6          spatstat.geom_2.1-0  
 [78] future.apply_1.7.0    reshape2_1.4.4        codetools_0.2-18      leiden_0.3.7          glue_1.4.2            evaluate_0.14         data.table_1.14.0    
 [85] png_0.1-7             vctrs_0.3.8           httpuv_1.6.0          polyclip_1.10-0       gtable_0.3.0          RANN_2.6.1            purrr_0.3.4          
 [92] spatstat.core_2.1-2   tidyr_1.1.3           scattermore_0.7       future_1.21.0         assertthat_0.2.1      ggplot2_3.3.3         xfun_0.22            
 [99] mime_0.10             xtable_1.8-4          later_1.2.0           survival_3.2-11       viridisLite_0.4.0     tibble_3.1.1          tinytex_0.31         
[106] cluster_2.1.2         globals_0.14.0        fitdistrplus_1.1-3    ellipsis_0.3.2        ROCR_1.0-11  

library("DESeq2")

dds <- DESeqDataSetFromMatrix(countData = cts,

                              colData = coldata,

                              design = ~ condition)

dds

Error in validObject(.Object): invalid class “SummarizedExperiment” object: undefined class for slot "NAMES" ("characterORNULL")
Traceback:

1. DESeqDataSetFromMatrix(countData = cts, colData = coldata, design = ~condition)
2. SummarizedExperiment(assays = SimpleList(counts = countData),
.     colData = colData, ...)
3. SummarizedExperiment(assays = SimpleList(counts = countData),
.     colData = colData, ...)
4. .local(assays, ...)
5. new_SummarizedExperiment(assays, ans_rownames, rowData, colData,
.     metadata)
6. new("SummarizedExperiment", NAMES = names, elementMetadata = rowData,
.     colData = colData, assays = assays, metadata = as.list(metadata))
7. initialize(value, ...)
8. initialize(value, ...)
9. validObject(.Object)
10. stop(msg, ": ", errors, domain = NA)

R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.3 LTS

Matrix products: default
BLAS: /ebio/abt3_projects/Christensenella_Project/anaconda3/envs/R_DEseq2/lib/R/lib/libRblas.so
LAPACK: /ebio/abt3_projects/Christensenella_Project/anaconda3/envs/R_DEseq2/lib/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=C.UTF-8       LC_NUMERIC=C           LC_TIME=C.UTF-8       
 [4] LC_COLLATE=C.UTF-8     LC_MONETARY=C.UTF-8    LC_MESSAGES=C.UTF-8   
 [7] LC_PAPER=C.UTF-8       LC_NAME=C              LC_ADDRESS=C          
[10] LC_TELEPHONE=C         LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C   

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] BiocInstaller_1.28.0       BiocParallel_1.12.0       
 [3] DESeq2_1.18.1              SummarizedExperiment_1.4.0
 [5] Biobase_2.38.0             GenomicRanges_1.30.0      
 [7] GenomeInfoDb_1.14.0        IRanges_2.12.0            
 [9] S4Vectors_0.16.0           BiocGenerics_0.24.0       
[11] ggplot2_2.2.1              tidyr_0.6.3               
[13] dplyr_0.7.0               

loaded via a namespace (and not attached):
 [1] locfit_1.5-9.1          Rcpp_0.12.13            lattice_0.20-34        
 [4] assertthat_0.2.0        digest_0.6.12           IRdisplay_0.4.4        
 [7] R6_2.2.1                plyr_1.8.4              repr_0.10              
[10] acepack_1.4.1           RSQLite_1.1-2           evaluate_0.10          
[13] zlibbioc_1.24.0         rlang_0.1.2             lazyeval_0.2.0         
[16] uuid_0.1-2              annotate_1.56.0         rpart_4.1-10           
[19] Matrix_1.2-7.1          splines_3.4.1           geneplotter_1.56.0     
[22] stringr_1.2.0           foreign_0.8-67          RCurl_1.95-4.8         
[25] munsell_0.4.3           compiler_3.4.1          nnet_7.3-12            
[28] tibble_1.3.3            GenomeInfoDbData_0.99.1 Hmisc_3.14-6           
[31] XML_3.98-1.6            crayon_1.3.2            bitops_1.0-6           
[34] grid_3.4.1              jsonlite_1.5            xtable_1.8-2           
[37] gtable_0.2.0            DBI_0.6-1               magrittr_1.5           
[40] scales_0.4.1            stringi_1.1.2           XVector_0.18.0         
[43] genefilter_1.60.0       latticeExtra_0.6-28     IRkernel_0.7.1         
[46] Formula_1.2-1           RColorBrewer_1.1-2      tools_3.4.1            
[49] glue_1.1.1              survival_2.40-1         AnnotationDbi_1.40.0   
[52] colorspace_1.3-2        cluster_2.0.6           memoise_1.1.0          
[55] pbdZMQ_0.2-6 

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355 votes

1 answers

Get the solution ↓↓↓

function insert($table, $args){
    
    $Query = "INSERT INTO ? VALUES(";
    $types="";
    foreach($args as $arg){
        $Query=$Query."?,";
        $type = gettype($arg);
        switch ($type) {
            case "string": 
                $types = $types."s";
                break;
            case "integer": 
            case "double": 
                $types = $types."d";
                break; 
        }
    }
    $Query=substr($Query, 0, -1);
    $Query=$Query.")";
    global $mysqli;
    $stmt=$mysqli->prepare($Query);
    echo $stmt;
    array_unshift($args, $table);
    array_unshift($args, $types);

    call_user_func_array(array($stmt, "bind_param"), $args);
    $stmt->execute();
}

Write your answer

710

votes

Answer

Solution:

Why, oh why would you want to create such function?

Don’t even think about creating such complex and utterly useless function. This will be your nightmare. Trust my advice and stop what you are doing right now.

If you are only starting with PHP then forget about mysqli. It is missing a lot of functionality and is very complex. Start learning PDO.

With PDO you do not need such functions.

Start by opening PDO connection:

$pdo = new PDO("mysql:host=localhost;dbname=db_name;charset=utf8mb4", 'username', 'password', [
    PDO::ATTR_ERRMODE => PDO::ERRMODE_EXCEPTION,
    PDO::ATTR_EMULATE_PREPARES => false
]);

Then you can execute a simple statement like this:

$pdo->prepare('INSERT INTO tableA(col1, col2) VALUES(?,?)')
    ->execute(['val1', 'val2']);

Binding unknown number of parameters is also quite simple.

$stmt = $pdo->prepare('SELECT * FROM TableA WHERE Id IN ('.implode(',', array_fill(0, count($ids), '?')).')');
$stmt->execute($ids);
$data = $stmt->fetchAll();

Just take a look how much simpler it is compared to your custom function.

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 — I am purging inactive userprofiles from 2012r2 RDS Collection host servers using powershell. 

 — Out of six servers, the command I’m using works on all but one.

 — All servers are Windows Server 2012r2 and have the exact same patching level, and are running Powershell 4.0

Here is the full syntax:    Get-CimInstance -Class Win32_UserProfile | Where-Object { $_.LocalPath.split(»)[-1] -eq ‘USERPROFILE’ } | Remove-CimInstance

Here is the resulting output: 

Get-CimInstance : Invalid class
At line:1 char:1
+ Get-CimInstance -Class Win32_UserProfile | Where-Object { $_.LocalPath.split(» …
+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    + CategoryInfo          : MetadataError: (rootcimv2:Win32_UserProfile:String) [Get-CimInstance], CimException
    + FullyQualifiedErrorId : HRESULT 0x80041010,Microsoft.Management.Infrastructure.CimCmdlets.GetCimInstanceCommand

NOTE:  If I just strip everything out and simply type «Get-CimInstance -Class Win32_UserProfile», I get the same error, so it’s not the Object, it’s the class.  

NOTE:  If I switch to Get-WMIObject, I get the same «Invalid Class» error, see below:

Get-WmiObject : Invalid class «Win32_Userprofile»
At line:1 char:1
+ Get-WmiObject Win32_Userprofile
+ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    + CategoryInfo          : InvalidType: (:) [Get-WmiObject], ManagementException
    + FullyQualifiedErrorId : GetWMIManagementException,Microsoft.PowerShell.Commands.GetWmiObjectCommand

___________________________________________________________________________________________

Here are my questions:

1.)  Has anyone seen this before, and if so, what did you do to resolve it?

2.)  Does anyone know if there is a way to rebuild/reinstall the WMI Classes?

3.)  As the same thing happens between Get-CimInstance and Get-WmiObject, can anyone point me toward what the underlying source/cause of the problem might be? 

I consider myself somewhat unskilled Powershell user, as I don’t use it much.   Regardless, these commands work fine on 5 out of 6 other identical servers.  

Any help is appreciated!, thanks.

-sMh-