rowStats: Row and Column Summary Statistics Based on Grouping

In kuwisdelu/matter: Out-of-core statistical computing and signal processing

Row and Column Summary Statistics Based on Grouping

Description

These functions perform calculation of summary statistics over matrix rows and columns for each level of a grouping variable.

Usage

## S4 method for signature 'ANY'
rowStats(x, stat, ..., BPPARAM = bpparam())

## S4 method for signature 'ANY'
colStats(x, stat, ..., BPPARAM = bpparam())

## S4 method for signature 'matter_mat'
rowStats(x, stat, ..., BPPARAM = bpparam())

## S4 method for signature 'matter_mat'
colStats(x, stat, ..., BPPARAM = bpparam())

## S4 method for signature 'sparse_mat'
rowStats(x, stat, ..., BPPARAM = bpparam())

## S4 method for signature 'sparse_mat'
colStats(x, stat, ..., BPPARAM = bpparam())

.rowStats(x, stat, group = NULL,
    na.rm = FALSE, simplify = TRUE, drop = TRUE,
    iter.dim = 1L, BPPARAM = bpparam(), ...)

.colStats(x, stat, group = NULL,
    na.rm = FALSE, simplify = TRUE, drop = TRUE,
    iter.dim = 2L, BPPARAM = bpparam(), ...)

Arguments

x	A matrix on which to calculate summary statistics.
stat	The name of summary statistics to compute over the rows or columns of a matrix. Allowable values include: "min", "max", "prod", "sum", "mean", "var", "sd", "any", "all", and "nnzero".
group	A factor or vector giving the grouping. If not provided, no grouping will be used.
na.rm	If TRUE, remove NA values before summarizing.
simplify	Simplify the results from a list to a vector or array. This also drops any additional attributes (besides names).
drop	If only a single summary statistic is calculated, return the results as a vector (or matrix) rather than a list.
iter.dim	The dimension to iterate over. Must be 1 or 2, where 1 indicates rows and 2 indicates columns.
BPPARAM	An optional instance of BiocParallelParam. See documentation for bplapply.
...	Additional arguments passed to chunk_rowapply() or chunk_colapply(), such as the number of chunks.

Details

The summary statistics methods are calculated over chunks of the matrix using s_colstats and s_rowstats. For matter objects, the iteration is performed over the major dimension for IO efficiency.

Value

A list for each stat requested, where each element is either a vector (if no grouping variable is provided) or a matrix where each column corresponds to a different level of group.

If drop=TRUE, and only a single statistic is requested, then the result will be unlisted and returned as a vector or matrix.

Author(s)

Kylie A. Bemis

See Also

colSums

Examples

register(SerialParam())

set.seed(1)

x <- matrix(runif(100^2), nrow=100, ncol=100)

g <- as.factor(rep(letters[1:5], each=20))

colStats(x, "mean", group=g)

kuwisdelu/matter documentation built on Oct. 19, 2024, 10:31 a.m.