downsample_matrix: Downsample the columns of a matrix to a target number

In tanaylab/tglkmeans: Efficient Implementation of K-Means++ Algorithm

Downsample the columns of a matrix to a target number

Description

This function takes a matrix and downsamples it to a target number of samples. It uses a random seed for reproducibility and allows for removing columns with small sums.

Usage

downsample_matrix(
  mat,
  target_n = NULL,
  target_q = NULL,
  seed = NULL,
  remove_columns = FALSE
)

Arguments

mat	An integer matrix to be downsampled. Can be a matrix or sparse matrix (dgCMatrix). If the matrix contains NAs, the function will run significantly slower. Values that are not integers will be coerced to integers using floor().
target_n	The target number of samples to downsample to.
target_q	A target quantile of sums to downsample to. Only one of 'target_n' or 'target_q' can be provided.
seed	The random seed for reproducibility (default is NULL)
remove_columns	Logical indicating whether to remove columns with small sums (default is FALSE)

Value

The downsampled matrix

Examples

mat <- matrix(1:12, nrow = 4)
downsample_matrix(mat, 2)

# Remove columns with small sums
downsample_matrix(mat, 12, remove_columns = TRUE)

# sparse matrix
mat_sparse <- Matrix::Matrix(mat, sparse = TRUE)
downsample_matrix(mat_sparse, 2)

# with a quantile
downsample_matrix(mat, target_q = 0.5)

tanaylab/tglkmeans documentation built on Jan. 27, 2024, 8:37 a.m.