colSums2 {DelayedMatrixStats} | R Documentation |
Calculates the sum for each row (column) in a matrix.
colSums2(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), ...) rowSums2(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), ...) ## S4 method for signature 'DelayedMatrix' colSums2(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), force_block_processing = FALSE, ...) ## S4 method for signature 'Matrix' colSums2(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), ...) ## S4 method for signature 'SolidRleArraySeed' colSums2(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), ...) ## S4 method for signature 'DelayedMatrix' rowSums2(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), force_block_processing = FALSE, ...) ## S4 method for signature 'Matrix' rowSums2(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), ...)
x |
A NxK DelayedMatrix. |
rows |
A |
cols |
A |
na.rm |
|
dim. |
An |
... |
Additional arguments passed to specific methods. |
force_block_processing |
|
The implementation of rowSums2()
and colSums2()
is
optimized for both speed and memory.
Returns a numeric
vector
of
length N (K).
# A DelayedMatrix with a 'matrix' seed dm_matrix <- DelayedArray(matrix(c(rep(1L, 5), as.integer((0:4) ^ 2), seq(-5L, -1L, 1L)), ncol = 3)) # A DelayedMatrix with a 'Matrix' seed dm_Matrix <- DelayedArray(Matrix::Matrix(c(rep(1L, 5), as.integer((0:4) ^ 2), seq(-5L, -1L, 1L)), ncol = 3)) colSums2(dm_matrix) # NOTE: Temporarily use verbose output to demonstrate which method is # which method is being used options(DelayedMatrixStats.verbose = TRUE) # By default, this uses a seed-aware method for a DelayedMatrix with a # 'SolidRleArraySeed' seed rowSums2(dm_Matrix) # Alternatively, can use the block-processing strategy rowSums2(dm_Matrix, force_block_processing = TRUE) options(DelayedMatrixStats.verbose = FALSE)