loomR save sparse matrix

[ccshao]

I tried to save the matrix as dense or sparse matrix into loom files, however, the size of the resulting loom files are nearly identical.

Once connected, in the loom file create with spare matrix, I still get the dense matrix. Would be possible to save the sparse matrix? I installed the loomR in develop branch.

> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Linux Mint 19.2

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1

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=de_DE.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=de_DE.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] Matrix_1.2-17     Seurat_3.1.0      loomR_0.2.1.9000  hdf5r_1.2.0      
 [5] R6_2.4.0          data.table_1.12.2 cowplot_1.0.0     ggplot2_3.2.1    
 [9] magrittr_1.5      colorout_1.2-1   

loaded via a namespace (and not attached):
 [1] nlme_3.1-141        tsne_0.1-3          bitops_1.0-6       
 [4] bit64_0.9-7         RcppAnnoy_0.0.12    RColorBrewer_1.1-2 
 [7] httr_1.4.1          useful_1.2.6        sctransform_0.2.0  
[10] tools_3.6.1         irlba_2.3.3         KernSmooth_2.23-15 
[13] uwot_0.1.3          lazyeval_0.2.2      colorspace_1.4-1   
[16] npsurv_0.4-0        withr_2.1.2         tidyselect_0.2.5   
[19] gridExtra_2.3       bit_1.1-14          compiler_3.6.1     
[22] plotly_4.9.0        caTools_1.17.1.2    scales_1.0.0       
[25] lmtest_0.9-37       ggridges_0.5.1      pbapply_1.4-1      
[28] stringr_1.4.0       digest_0.6.20       R.utils_2.9.0      
[31] pkgconfig_2.0.2     htmltools_0.3.6     bibtex_0.4.2       
[34] htmlwidgets_1.3     rlang_0.4.0         RApiSerialize_0.1.0
[37] zoo_1.8-6           jsonlite_1.6        ica_1.0-2          
[40] gtools_3.8.1        dplyr_0.8.3         R.oo_1.22.0        
[43] Rcpp_1.0.2          munsell_0.5.0       ape_5.3            
[46] reticulate_1.13     R.methodsS3_1.7.1   stringi_1.4.3      
[49] gbRd_0.4-11         MASS_7.3-51.4       gplots_3.0.1.1     
[52] Rtsne_0.15          plyr_1.8.4          grid_3.6.1         
[55] parallel_3.6.1      gdata_2.18.0        listenv_0.7.0      
[58] ggrepel_0.8.1       crayon_1.3.4        lattice_0.20-38    
[61] splines_3.6.1       SDMTools_1.1-221.1  pillar_1.4.2       
[64] igraph_1.2.4.1      future.apply_1.3.0  reshape2_1.4.3     
[67] codetools_0.2-16    leiden_0.3.1        glue_1.3.1         
[70] lsei_1.2-0          metap_1.1           RcppParallel_4.4.3 
[73] png_0.1-7           Rdpack_0.11-0       gtable_0.3.0       
[76] RANN_2.6.1          purrr_0.3.2         tidyr_0.8.3        
[79] qs_0.18.3           future_1.14.0       assertthat_0.2.1   
[82] rsvd_1.0.2          survival_2.44-1.1   viridisLite_0.3.0  
[85] tibble_2.1.3        cluster_2.1.0       globals_0.12.4     
[88] fitdistrplus_1.0-14 ROCR_1.0-7         

[timothy-barry]

Curious if there's been an update here?