big_cor: Correlation

View source: R/crossprodSelf.R

big_corR Documentation

Correlation

Description

Compute the (Pearson) correlation matrix of a Filebacked Big Matrix.

Usage

big_cor(
  X,
  ind.row = rows_along(X),
  ind.col = cols_along(X),
  block.size = block_size(nrow(X)),
  backingfile = tempfile(tmpdir = getOption("FBM.dir"))
)

Arguments

X

An object of class FBM.

ind.row

An optional vector of the row indices that are used. If not specified, all rows are used. Don't use negative indices.

ind.col

An optional vector of the column indices that are used. If not specified, all columns are used. Don't use negative indices.

block.size

Maximum number of columns read at once. Default uses block_size.

backingfile

Path to the file storing the FBM data on disk. An extension ".bk" will be automatically added. Default stores in the temporary directory, which you can change using global option "FBM.dir".

Value

A temporary FBM, with the following two attributes:

  • a numeric vector center of column scaling,

  • a numeric vector scale of column scaling.

Matrix parallelization

Large matrix computations are made block-wise and won't be parallelized in order to not have to reduce the size of these blocks. Instead, you can use the MKL or OpenBLAS in order to accelerate these block matrix computations. You can control the number of cores used by these optimized matrix libraries with bigparallelr::set_blas_ncores().

See Also

cor big_crossprodSelf

Examples

X <- FBM(13, 17, init = rnorm(221))

# Comparing with cor
K <- big_cor(X)
class(K)
dim(K)
K$backingfile

true <- cor(X[])
all.equal(K[], true)

# Using only half of the data
n <- nrow(X)
ind <- sort(sample(n, n/2))
K2 <- big_cor(X, ind.row = ind)

true2 <- cor(X[ind, ])
all.equal(K2[], true2)

bigstatsr documentation built on Sept. 11, 2024, 7:08 p.m.