I have a strange error, that I don't think is related to the input data, about dtype('float64') to dtype('int64') conversion. Is it possible that from the A2 python connection something strange is happening here?

Thanks a lot

Offending code

library(basilisk)
metacells_env <- BasiliskEnvironment(
  envname = "metacells_env",
  pkgname = "HPCell",
  packages = c("numpy==1.24.3"),  # Upgrade numpy to a version compatible with Python 3.10
  pip = c("metacells==0.9.4", "anndata==0.10.9")  # Use pip to install metacells
)
basiliskStart(metacells_env)

mc <- reticulate::import("metacells", delay_load = TRUE)
np <- reticulate::import("numpy", delay_load = TRUE)

my_anndata = anndata$AnnData(X = matrix(as.integer(rpois(200, lambda = 5)), nrow = 20, ncol = 10) )

mc$pl$divide_and_conquer_pipeline(my_anndata, random_seed=123456)


# ERROR

set unnamed.var[selected_gene]: * -> False
set unnamed.var[rare_gene]: 0 true (0%) out of 36412 bools
set unnamed.var[rare_gene_module]: 36412 int32 elements with all outliers (100%)
set unnamed.obs[cells_rare_gene_module]: 4860 int32 elements with all outliers (100%)
set unnamed.obs[rare_cell]: 0 true (0%) out of 4860 bools
Error in py_call_impl(callable, call_args$unnamed, call_args$named) : 
  TypeError: Cannot cast scalar from dtype('float64') to dtype('int64') according to the rule 'safe'


sessionInfo()
R version 4.4.1 (2024-06-14)
Platform: x86_64-pc-linux-gnu
Running under: Red Hat Enterprise Linux 9.4 (Plow)

Matrix products: default
BLAS:   /stornext/System/data/software/rhel/9/base/tools/R/4.4.1/lib64/R/lib/libRblas.so 
LAPACK: /home/users/allstaff/mangiola.s/.cache/R/basilisk/1.16.0/HPCell/0.3.7/metacells_env/lib/libmkl_rt.so.1;  LAPACK version 3.9.0

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

time zone: Australia/Melbourne
tzcode source: system (glibc)

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

other attached packages:
 [1] SummarizedExperiment_1.34.0 Biobase_2.64.0              GenomicRanges_1.56.1        GenomeInfoDb_1.40.1         IRanges_2.38.1             
 [6] S4Vectors_0.42.1            BiocGenerics_0.50.0         MatrixGenerics_1.16.0       matrixStats_1.4.1           basilisk_1.16.0            
[11] reticulate_1.39.0           CuratedAtlasQueryR_1.4.7    crew.cluster_0.3.2          HPCell_0.3.7                shinyBS_0.61.1             
[16] stringr_1.5.1               purrr_1.0.2                 tibble_3.2.1                glue_1.8.0                  targets_1.8.0.9003         
[21] duckdb_1.0.0-2              DBI_1.2.3                   dplyr_1.1.4                 arrow_17.0.0.1             

loaded via a namespace (and not attached):
  [1] igraph_2.1.1                      ica_1.0-3                         plotly_4.10.4                     SingleR_2.6.0                    
  [5] scater_1.32.1                     zlibbioc_1.50.0                   tidyselect_1.2.1                  bit_4.5.0                        
  [9] lattice_0.22-6                    rjson_0.2.23                      blob_1.2.4                        S4Arrays_1.4.1                   
 [13] parallel_4.4.1                    seqLogo_1.70.0                    png_0.1-8                         cli_3.6.3                        
 [17] ProtGenerics_1.36.0               goftest_1.2-3                     gargle_1.5.2                      BiocIO_1.14.0                    
 [21] bluster_1.14.0                    basilisk.utils_1.16.0             BiocNeighbors_1.22.0              tarchetypes_0.10.0               
 [25] Signac_1.14.0                     uwot_0.2.2                        curl_5.2.3                        mime_0.12                        
 [29] leiden_0.4.3.1                    V8_5.0.0                          stringi_1.8.4                     ids_1.0.1                        
 [33] backports_1.5.0                   XML_3.99-0.17                     httpuv_1.6.15                     AnnotationDbi_1.66.0             
 [37] magrittr_2.0.3                    rappdirs_0.3.3                    splines_4.4.1                     RcppRoll_0.3.1                   
 [41] nanonext_1.3.0                    RApiSerialize_0.1.4               DT_0.33                           sctransform_0.4.1                
 [45] ggbeeswarm_0.7.2                  HDF5Array_1.32.1                  withr_3.0.1                       rprojroot_2.0.4                  
 [49] xgboost_1.7.8.1                   tidySummarizedExperiment_1.14.0   lmtest_0.9-40                     BiocManager_1.30.25              
 [53] rtracklayer_1.64.0                htmlwidgets_1.6.4                 fs_1.6.4                          biomaRt_2.60.1                   
 [57] SingleCellExperiment_1.26.0       ggrepel_0.9.6                     SparseArray_1.4.8                 cellranger_1.1.0                 
 [61] tidyseurat_0.8.1                  annotate_1.82.0                   zoo_1.8-12                        JASPAR2020_0.99.10               
 [65] XVector_0.44.0                    knitr_1.48                        TFBSTools_1.42.0                  UCSC.utils_1.0.0                 
 [69] TFMPvalue_0.0.9                   secretbase_1.0.3                  fansi_1.0.6                       patchwork_1.3.0                  
 [73] caTools_1.18.3                    grid_4.4.1                        data.table_1.16.2                 rhdf5_2.48.0                     
 [77] pwalign_1.0.0                     R.oo_1.26.0                       poweRlaw_0.80.0                   RSpectra_0.16-2                  
 [81] irlba_2.3.5.1                     alabaster.schemas_1.4.0           fastDummies_1.7.4                 ellipsis_0.3.2                   
 [85] base64url_1.4                     lazyeval_0.2.2                    yaml_2.3.10                       tidySingleCellExperiment_1.15.5  
 [89] survival_3.7-0                    scattermore_1.2                   BiocVersion_3.19.1                crayon_1.5.3                     
 [93] mirai_1.3.0                       RcppAnnoy_0.0.22                  RColorBrewer_1.1-3                tidyr_1.3.1                      
 [97] progressr_0.14.0                  later_1.3.2                       tidybulk_1.17.3                   ggridges_0.5.6                   
[101] codetools_0.2-20                  Seurat_5.1.0                      KEGGREST_1.44.1                   Rtsne_0.17                       
[105] limma_3.60.4                      Rsamtools_2.20.0                  filelock_1.0.3                    pkgconfig_2.0.3                  
[109] xml2_1.3.6                        spatstat.univar_3.0-1             GenomicAlignments_1.40.0          alabaster.base_1.4.2             
[113] spatstat.sparse_3.1-0             BSgenome_1.72.0                   viridisLite_0.4.2                 xtable_1.8-4                     
[117] plyr_1.8.9                        httr_1.4.7                        tools_4.4.1                       globals_0.16.3                   
[121] SeuratObject_5.0.2                pkgbuild_1.4.4                    checkmate_2.3.2                   beeswarm_0.4.0                   
[125] broom_1.0.7                       nlme_3.1-166                      loo_2.8.0                         ExperimentHub_2.12.0             
[129] dbplyr_2.5.0                      hdf5r_1.3.11                      shinyjs_2.1.0                     lme4_1.1-35.5                    
[133] assertthat_0.2.1                  digest_0.6.37                     Matrix_1.7-0                      dir.expiry_1.12.0                
[137] farver_2.1.2                      tzdb_0.4.0                        AnnotationFilter_1.28.0           reshape2_1.4.4                   
[141] viridis_0.6.5                     DirichletMultinomial_1.46.0       cachem_1.1.0                      BiocFileCache_2.12.0             
[145] polyclip_1.10-7                   generics_0.1.3                    Biostrings_2.72.1                 googledrive_2.1.1                
[149] presto_1.0.0                      parallelly_1.38.0                 statmod_1.5.0                     here_1.0.1                       
[153] RcppHNSW_0.6.0                    ScaledMatrix_1.12.0               minqa_1.2.8                       pbapply_1.7-2                    
[157] httr2_1.0.3                       job_0.3.1                         spam_2.11-0                       dqrng_0.4.1                      
[161] utf8_1.2.4                        scDblFinder_1.18.0                StanHeaders_2.32.10               gtools_3.9.5                     
[165] preprocessCore_1.66.0             alabaster.se_1.4.1                crew_0.10.0                       gridExtra_2.3                    
[169] shiny_1.9.1                       GenomeInfoDbData_1.2.12           R.utils_2.12.3                    rhdf5filters_1.16.0              
[173] RCurl_1.98-1.16                   memoise_2.0.1                     scales_1.3.0                      R.methodsS3_1.8.2                
[177] googlesheets4_1.1.1               gypsum_1.0.1                      future_1.34.0                     RANN_2.6.2                       
[181] stringfish_0.16.0                 spatstat.data_3.1-2               rstudioapi_0.16.0                 zellkonverter_1.14.1             
[185] cluster_2.1.6                     QuickJSR_1.3.1                    spatstat.utils_3.1-0              hms_1.1.3                        
[189] fitdistrplus_1.2-1                munsell_0.5.1                     cowplot_1.1.3                     colorspace_2.1-1                 
[193] rlang_1.1.4                       DelayedMatrixStats_1.26.0         sparseMatrixStats_1.16.0          dotCall64_1.2                    
[197] shinydashboard_0.7.2              scuttle_1.14.0                    xfun_0.48                         alabaster.matrix_1.4.2           
[201] CNEr_1.40.0                       abind_1.4-8                       EnsDb.Hsapiens.v86_2.99.0         rstan_2.32.6                     
[205] celldex_1.14.0                    Rhdf5lib_1.26.0                   ggplot2_3.5.1                     readr_2.1.5                      
[209] bitops_1.0-9                      ps_1.8.0                          promises_1.3.0                    inline_0.3.19                    
[213] RSQLite_2.3.7                     getip_0.1-4                       DelayedArray_0.30.1               GO.db_3.19.1                     
[217] compiler_4.4.1                    alabaster.ranges_1.4.2            prettyunits_1.2.0                 boot_1.3-30                      
[221] beachmat_2.20.0                   ttservice_0.4.1                   listenv_0.9.1                     BSgenome.Hsapiens.UCSC.hg38_1.4.5
[225] Rcpp_1.0.13                       AnnotationHub_3.12.0              edgeR_4.2.1                       BiocSingular_1.20.0              
[229] tensor_1.5                        autometric_0.0.5                  qs_0.27.2                         MASS_7.3-61                      
[233] progress_1.2.3                    uuid_1.2-1                        BiocParallel_1.38.0               ggupset_0.4.0                    
[237] spatstat.random_3.3-2             R6_2.5.1                          Azimuth_0.5.0                     fastmap_1.2.0                    
[241] fastmatch_1.1-4                   vipor_0.4.7                       ensembldb_2.28.1                  ROCR_1.0-11                      
[245] SeuratDisk_0.0.0.9021             rsvd_1.0.5                        gtable_0.3.5                      KernSmooth_2.23-24               
[249] miniUI_0.1.1.1                    deldir_2.0-4                      htmltools_0.5.8.1                 RcppParallel_5.1.9               
[253] bit64_4.5.2                       spatstat.explore_3.3-2            lifecycle_1.0.4                   processx_3.8.4                   
[257] nloptr_2.1.1                      callr_3.7.6                       restfulr_0.0.15                   vctrs_0.6.5                      
[261] spatstat.geom_3.3-3               scran_1.32.0                      sp_2.1-4                          SeuratData_0.2.2.9001            
[265] future.apply_1.11.2               pracma_2.4.4                      pillar_1.9.0                      GenomicFeatures_1.56.0           
[269] DropletUtils_1.24.0               metapod_1.12.0                    locfit_1.5-9.10                   jsonlite_1.8.9

I focused on the main data, while the problem was the seed class. This solves the problem

mc$pl$divide_and_conquer_pipeline(my_anndata, random_seed=123456L)