The functions fromSparseMatrix
and toSparseMatrix
help in storing
(and retrieving) sparse matrices using a TileDB backend.
fromSparseMatrix( obj, uri, cell_order = "ROW_MAJOR", tile_order = "ROW_MAJOR", filter = "ZSTD", capacity = 10000L ) toSparseMatrix(uri)
obj | A sparse matrix object. |
---|---|
uri | A character variable with an Array URI. |
cell_order | A character variable with one of the TileDB cell order values, default is “COL_MAJOR”. |
tile_order | A character variable with one of the TileDB tile order values, default is “COL_MAJOR”. |
filter | A character variable vector, defaults to ‘ZSTD’, for one or more filters to be applied to each attribute; |
capacity | A integer value with the schema capacity, default is 10000. |
Null, invisibly.
ctx <- tiledb_ctx(limitTileDBCores()) if (FALSE) { if (requireNamespace("Matrix", quietly=TRUE)) { library(Matrix) set.seed(123) # just to fix it mat <- matrix(0, nrow=20, ncol=10) mat[sample(seq_len(200), 20)] <- seq(1, 20) spmat <- as(mat, "dgTMatrix") # sparse matrix in dgTMatrix format uri <- "sparse_matrix" fromSparseMatrix(spmat, uri) # now written chk <- toSparseMatrix(uri) # and re-read print(chk) all.equal(spmat, chk) } }