R/00-classes.r

In kazaam: Tools for Tall Distributed Matrices

#' Class shaq
#' 
#' An S4 container for a distributed tall/skinny matrix.
#' 
#' @details
#' The (conceptual) global (non-distributed) matrix should be distributed by
#' row, meaning that each submatrix should own all of the columns of the global
#' matrix.  Most methods assume no other real structure, however for best
#' performance (and for the methods which require it), one should try to
#' organize their distributed data in a particular way.
#' 
#' First, adjacent MPI ranks should hold adjacent rows.  So if the last row that
#' rank \code{k} owns is \code{i}, then the first row that rank \code{k+1} owns 
#' should be row \code{i+1}.  Additionally, any method that operates on two (or
#' more) shaq objects, the two shaqs should be distributed identically.  By this
#' we mean that if the number of rows shaq \code{A} owns on rank \code{k} is
#' \code{k_i}, then the number of rows shaq \code{B} owns on rank \code{k}
#' should also be \code{k_i}.
#' 
#' Finally, for best performance, one should generally try to keep the number of
#' rows "balanced" (roughly equal) across processes, with perhaps the last "few"
#' having one less row than the others.
#' 
#' @slot DATA
#' The local submatrix.
#' @slot nrows, ncols
#' The global matrix dimension.
#' 
#' @seealso
#' \code{\link{shaq}}
#' 
#' @name shaq-class
#' @docType class
setClass(
  Class="shaq", 
  representation=representation(
    Data="matrix",
    nrows="numeric",
    ncols="numeric"
    # balanced="logical"
  ),
  
  prototype=prototype(
    Data=matrix(nrow=0, ncol=0),
    nrows=0,
    ncols=0
    # balanced=NA
  )
)