doFuture examples

DESCRIPTION

@@ -49,6 +49,7 @@ RoxygenNote: 7.3.1
 Suggests: 
     ggplot2,
     doParallel,
+    doFuture,
     mlbench,
     knitr,
     rmarkdown,

R/adversarial_rf.R

@@ -16,7 +16,7 @@
 #' @param prune Impose \code{min_node_size} by pruning? 
 #' @param verbose Print discriminator accuracy after each round?
 #' @param parallel Compute in parallel? Must register backend beforehand, e.g. 
-#'   via \code{doParallel}.
+#'   via \code{doParallel} or \code{doFuture}; see examples.
 #' @param ... Extra parameters to be passed to \code{ranger}.
 #' 
 #' @details 
@@ -83,6 +83,15 @@
 #' evi <- data.frame(Species = "setosa")
 #' expct(psi, query = "Sepal.Length", evidence = evi)
 #' 
+#' \dontrun{
+#' # Parallelization with doParallel
+#' doParallel::registerDoParallel(cores = 4)
+#'
+#' # ... or with doFuture
+#' doFuture::registerDoFuture()
+#' future::plan("multisession", workers = 4)
+#' }
+#' 
 #' @seealso
 #' \code{\link{arf}}, \code{\link{forde}}, \code{\link{forge}}, \code{\link{expct}}, \code{\link{lik}}
 #' 

R/arf-package.R

@@ -27,6 +27,15 @@
 #' # Expectation of Sepal.Length for class setosa
 #' evi <- data.frame(Species = "setosa")
 #' expct(psi, query = "Sepal.Length", evidence = evi)
+#' 
+#' \dontrun{
+#' # Parallelization with doParallel
+#' doParallel::registerDoParallel(cores = 4)
+#'
+#' # ... or with doFuture
+#' doFuture::registerDoFuture()
+#' future::plan("multisession", workers = 4)
+#' }
 "_PACKAGE"
 
 ## usethis namespace: start

R/expct.R

@@ -20,7 +20,7 @@
 #' @param stepsize Stepsize defining number of evidence rows handled in one for each step.
 #'   Defaults to nrow(evidence)/num_registered_workers for \code{parallel == TRUE}.
 #' @param parallel Compute in parallel? Must register backend beforehand, e.g. 
-#'   via \code{doParallel}.
+#'   via \code{doParallel} or \code{doFuture}; see examples.
 #'   
 #' @details 
 #' This function computes expected values for any subset of features, optionally 
@@ -70,6 +70,15 @@
 #' evi[2, 2] <- NA_real_
 #' x_synth <- expct(psi, evidence = evi)
 #' 
+#' \dontrun{
+#' # Parallelization with doParallel
+#' doParallel::registerDoParallel(cores = 4)
+#'
+#' # ... or with doFuture
+#' doFuture::registerDoFuture()
+#' future::plan("multisession", workers = 4)
+#' }
+#' 
 #' @seealso
 #' \code{\link{arf}}, \code{\link{adversarial_rf}}, \code{\link{forde}}, \code{\link{forge}}, \code{\link{lik}}
 #' 

R/forde.R

@@ -25,7 +25,7 @@
 #'   data. The gap between lower and upper bounds is expanded by a factor of 
 #'   \code{1 + epsilon}. 
 #' @param parallel Compute in parallel? Must register backend beforehand, e.g. 
-#'   via \code{doParallel}.
+#'   via \code{doParallel} or \code{doFuture}; see examples.
 #'   
 #'   
 #' @details 
@@ -89,6 +89,15 @@
 #' evi <- data.frame(Species = "setosa")
 #' expct(psi, query = "Sepal.Length", evidence = evi)
 #' 
+#' \dontrun{
+#' # Parallelization with doParallel
+#' doParallel::registerDoParallel(cores = 4)
+#'
+#' # ... or with doFuture
+#' doFuture::registerDoFuture()
+#' future::plan("multisession", workers = 4)
+#' }
+#' 
 #' @seealso
 #' \code{\link{arf}}, \code{\link{adversarial_rf}}, \code{\link{forge}}, \code{\link{expct}}, \code{\link{lik}}
 #' 

R/forge.R

@@ -16,7 +16,7 @@
 #' @param stepsize Stepsize defining number of evidence rows handled in one for each step.
 #'   Defaults to nrow(evidence)/num_registered_workers for \code{parallel == TRUE}.
 #' @param parallel Compute in parallel? Must register backend beforehand, e.g. 
-#'   via \code{doParallel}.
+#'   via \code{doParallel} or \code{doFuture}; see examples.
 #' @param n_synth Number of synthetic samples to generate.
 #'
 #' @details  
@@ -84,6 +84,15 @@
 #' n_leaves <- nrow(psi$forest)
 #' evi <- data.frame(f_idx = psi$forest$f_idx, wt = rexp(n_leaves))
 #' x_synth <- forge(psi, n_synth = 100, evidence = evi)
+#' 
+#' \dontrun{
+#' # Parallelization with doParallel
+#' doParallel::registerDoParallel(cores = 4)
+#'
+#' # ... or with doFuture
+#' doFuture::registerDoFuture()
+#' future::plan("multisession", workers = 4)
+#' }
 #'
 #' @seealso
 #' \code{\link{arf}}, \code{\link{adversarial_rf}}, \code{\link{forde}}, \code{\link{expct}}, \code{\link{lik}}

R/lik.R

@@ -22,7 +22,7 @@
 #'   However, with large samples or many trees, it can be more memory efficient 
 #'   to split the data into batches. This has no impact on results.
 #' @param parallel Compute in parallel? Must register backend beforehand, e.g. 
-#'   via \code{doParallel}.
+#'   via \code{doParallel} or \code{doFuture}; see examples.
 #'   
 #'   
 #' @details 
@@ -76,6 +76,15 @@
 #'                   Petal.Width = ">0.3")
 #' lik(psi, query = iris[1, 1:3], evidence = evi)
 #' 
+#' \dontrun{
+#' # Parallelization with doParallel
+#' doParallel::registerDoParallel(cores = 4)
+#'
+#' # ... or with doFuture
+#' doFuture::registerDoFuture()
+#' future::plan("multisession", workers = 4)
+#' }
+#' 
 #' @seealso
 #' \code{\link{arf}}, \code{\link{adversarial_rf}}, \code{\link{forde}}, \code{\link{forge}}, \code{\link{expct}}
 #' 

R/utils.R

@@ -202,7 +202,7 @@ post_x <- function(x, params, round = TRUE) {
 #' @param row_mode Interpretation of rows in multi-row conditions.
 #' @param stepsize Stepsize defining number of condition rows handled in one for each step.
 #' @param parallel Compute in parallel? Must register backend beforehand, e.g. 
-#'   via \code{doParallel}.
+#'   via \code{doParallel} or \code{doFuture}; see examples.
 #'   
 #' @return List with conditions (\code{evidence_input}), prepared conditions (\code{evidence_prepped})
 #'   and leaves that match the conditions in evidence with continuous data (\code{cnt})