colAvgsPerRowSet {DelayedMatrixStats} | R Documentation |
Applies a row-by-row (column-by-column) averaging function to equally-sized subsets of matrix columns (rows). Each subset is averaged independently of the others.
colAvgsPerRowSet(X, W = NULL, cols = NULL, S, FUN = colMeans, ..., tFUN = FALSE) rowAvgsPerColSet(X, W = NULL, rows = NULL, S, FUN = rowMeans, ..., tFUN = FALSE) ## S4 method for signature 'DelayedMatrix' colAvgsPerRowSet(X, W = NULL, cols = NULL, S, FUN = colMeans, ..., force_block_processing = FALSE, tFUN = FALSE) ## S4 method for signature 'DelayedMatrix' rowAvgsPerColSet(X, W = NULL, rows = NULL, S, FUN = rowMeans, ..., force_block_processing = FALSE, tFUN = FALSE)
X |
A NxM DelayedMatrix. |
W |
|
cols |
A |
S |
An |
FUN |
The row-by-row (column-by-column) |
... |
Additional arguments passed to specific methods. |
tFUN |
If |
rows |
A |
force_block_processing |
|
If argument S
is a single column vector with indices 1:N
, then
rowAvgsPerColSet(X, S = S, FUN = rowMeans)
gives the same result as
rowMeans(X)
. Analogously, for colAvgsPerRowSet()
.
Returns a numeric
JxN (MxJ)
matrix
, where row names equal rownames(X)
(colnames(S)
) and column names colnames(S)
(colnames(X)
).
# A DelayedMatrix with a 'DataFrame' seed dm_DF <- DelayedArray(S4Vectors::DataFrame(C1 = rep(1L, 5), C2 = as.integer((0:4) ^ 2), C3 = seq(-5L, -1L, 1L))) colAvgsPerRowSet(dm_DF, S = matrix(1:2, ncol = 2)) rowAvgsPerColSet(dm_DF, S = matrix(1:2, ncol = 1))