colMedians {DelayedMatrixStats} | R Documentation |
Calculates the median for each row (column) in a matrix.
colMedians(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), ...) rowMedians(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), ...) ## S4 method for signature 'DelayedMatrix' colMedians(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), force_block_processing = FALSE, ...) ## S4 method for signature 'DelayedMatrix' rowMedians(x, rows = NULL, cols = NULL, na.rm = FALSE, dim. = dim(x), force_block_processing = FALSE, ...)
x |
A NxK DelayedMatrix. |
rows |
A |
cols |
A |
na.rm |
|
dim. |
An |
... |
Additional arguments passed to specific methods. |
force_block_processing |
|
The implementation of rowMedians()
and colMedians()
is
optimized for both speed and memory. To avoid coercing to
double
s (and hence memory allocation), there is a
special implementation for integer
matrices. That is,
if x
is an integer
matrix
,
then rowMedians(as.double(x))
(rowMedians(as.double(x))
) would
require three times the memory of rowMedians(x)
(colMedians(x)
), but all this is avoided.
Returns a numeric
vector
of
length N (K).
See rowWeightedMedians()
and
colWeightedMedians()
for weighted medians.
For mean estimates, see rowMeans2()
and
rowMeans()
.
# 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)) colMedians(dm_Matrix) rowMedians(dm_Matrix)