## ----include=FALSE------------------------------------------------------------
old_options <- options(
  max.print = 10, # Set the maximum number of rows to display
  width = 80 # Set the maximum number of columns to display
)

## ----message=F----------------------------------------------------------------
library(dbMatrix)
library(Matrix)

## -----------------------------------------------------------------------------
set.seed(42)
dgc <- Matrix::rsparsematrix(100, 50, density = 0.1, rand.x = function(n) rpois(n, 5) + 1)
rownames(dgc) <- paste0("gene_", seq_len(100))
colnames(dgc) <- paste0("cell_", seq_len(50))

dplyr::glimpse(dgc)

## -----------------------------------------------------------------------------
# create dbSparseMatrix from the same dgc
con <- DBI::dbConnect(duckdb::duckdb(), ":memory:")

sparse <- dbMatrix(
  value = dgc,
  con = con,
  name = "test_matrix",
  class = "dbSparseMatrix",
  overwrite = TRUE
)

# preview
# show function aims to emulate the show method for dgCMatrix
head(sparse)

## -----------------------------------------------------------------------------
dbMatrix::t(sparse)

## -----------------------------------------------------------------------------
dbMatrix::colMeans(sparse)

## -----------------------------------------------------------------------------
dbMatrix::colSums(sparse)

## -----------------------------------------------------------------------------
dbMatrix::rowMeans(sparse)

## -----------------------------------------------------------------------------
dbMatrix::rowSums(sparse)

## -----------------------------------------------------------------------------
dim(sparse)

dim(dgc)

## -----------------------------------------------------------------------------
all.equal(dbMatrix::colMeans(sparse, memory = TRUE, names = TRUE), Matrix::colMeans(dgc))

all.equal(dbMatrix::colSums(sparse, memory = TRUE, names = TRUE), Matrix::colSums(dgc))

all.equal(dbMatrix::rowMeans(sparse, memory = TRUE, names = TRUE), Matrix::rowMeans(dgc))

all.equal(dbMatrix::rowSums(sparse, memory = TRUE, names = TRUE), Matrix::rowSums(dgc))

## ----eval=TRUE, message=FALSE, warning=FALSE----------------------------------
# Create a dense matrix directly
set.seed(42)
mat <- matrix(rnorm(100), nrow = 10, ncol = 10)
rownames(mat) <- paste0("row_", 1:10)
colnames(mat) <- paste0("col_", 1:10)

# Create dbDenseMatrix
con2 <- DBI::dbConnect(duckdb::duckdb(), ":memory:")
dense <- dbMatrix(
  value = mat,
  con = con2,
  name = "dense_matrix",
  class = "dbDenseMatrix",
  overwrite = TRUE
)

# preview
dense

## -----------------------------------------------------------------------------
dbMatrix::t(dense)

## -----------------------------------------------------------------------------
dbMatrix::colMeans(dense)

## -----------------------------------------------------------------------------
dbMatrix::colSums(dense)

## -----------------------------------------------------------------------------
dbMatrix::rowMeans(dense)

## -----------------------------------------------------------------------------
dbMatrix::rowSums(dense)

## -----------------------------------------------------------------------------
dbMatrix::mean(dense)

## -----------------------------------------------------------------------------
dim(dense)

## -----------------------------------------------------------------------------
DBI::dbDisconnect(con, shutdown = TRUE)
DBI::dbDisconnect(con2, shutdown = TRUE)
options(old_options)

## ----eval=TRUE, message=FALSE-------------------------------------------------
sessionInfo()