R/sparsernorm.R

In egenn/rtemis: Machine Learning and Visualization

# sparsernorm.R
# ::rtemis::
# E.D. Gennatas www.lambdamd.org

#' Sparse rnorm
#'
#' A sparse version of `stats::rnorm`
#' Outputs a vector where a fraction of values are zeros (determined by `sparseness`)
#' and the rest are drawn from a random normal distribution using `stats::rnorm`
#'
#' @param n Integer: Length of output vector
#' @param sparseness Float (0, 1): Fraction of required nonzero elements, i.e. output will have
#' `round(sparseness * n) nonzero elements`.
#' If `sparseness = 0`, a vector of zeros length `n` is returned,
#' if `sparseness = 1`, `rnorm(n, mean, sd)` is returned.
#' Default = 0.1
#' @param mean Float: Target mean of nonzero elements, passed to `stats::rnorm` Default = 0
#' @param sd Float: Target sd of nonzero elements, passed to `stats::rnorm` Default = 1
#' @author E.D. Gennatas
#' @export

sparsernorm <- function(n,
                        sparseness = .1,
                        mean = 0,
                        sd = 1) {
  if (sparseness > 0 && sparseness < 1) {
    .n <- round(sparseness * n)
    .rnorm <- rnorm(.n, mean = mean, sd = sd)
    out <- rep(0, n)
    index <- sample(n, .n)
    out[index] <- .rnorm
    out
  } else if (sparseness == 0) {
    rep(0, n)
  } else {
    rnorm(n, mean = mean, sd = sd)
  }
} # rtemis::sparsernorm