% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RcppExports.R
\name{rcpp_hdf5dataset_crossprod}
\alias{rcpp_hdf5dataset_crossprod}
\title{Cross product for HDF5 datasets (R6 wrapper)}
\usage{
rcpp_hdf5dataset_crossprod(
  ptr_a,
  ptr_b,
  paral = NULL,
  block_size = NULL,
  threads = NULL,
  compression = NULL,
  outgroup = NULL,
  outdataset = NULL
)
}
\arguments{
\item{ptr_a}{External pointer (SEXP) for matrix A}

\item{ptr_b}{External pointer (SEXP) for matrix B}

\item{paral}{Logical or NULL; enable OpenMP parallelisation}

\item{block_size}{Integer or NULL; block size (NULL = auto)}

\item{threads}{Integer or NULL; thread count when \code{paral = TRUE}}

\item{outgroup}{Character or NULL. Output group in the HDF5 file.
Default \code{"OUTPUT"}.}

\item{outdataset}{Character or NULL. Output dataset name.
Default \code{"CrossProd_A"} (single matrix) or
\code{"CrossProd_A_x_B"} (two matrices).}
}
\value{
Named list with \code{filename} and \code{path} of the result.
}
\description{
Computes \code{t(A) \%*\% B} using the dedicated BigDataStatMeth
block-wise cross-product algorithm. When A and B refer to the same
dataset, the symmetric optimisation (\code{bisSymetric = TRUE}) is
applied automatically.
}
\keyword{internal}
