From 0bd09ca231c7d74a10ed44f32bb2d4cdc056940d Mon Sep 17 00:00:00 2001
From: Mitch <mitch.ohara-wild@monash.edu>
Date: Sun, 17 Jan 2021 21:20:25 +1100
Subject: [PATCH] Add progress reporting to model() docs

---
 R/model.R    |  7 +++++++
 man/model.Rd | 10 ++++++++++
 2 files changed, 17 insertions(+)

diff --git a/R/model.R b/R/model.R
index 73685cf8..726626f8 100644
--- a/R/model.R
+++ b/R/model.R
@@ -29,6 +29,11 @@ model <- function(.data, ...){
 #' [`future::plan()`] before estimating the models, they will be computed 
 #' according to that plan.
 #' 
+#' @section Progress:
+#' 
+#' Progress on model estimation can be obtained by wrapping the code with 
+#' `progressr::with_progress()`. Further customisation on how progress is 
+#' reported can be controlled using the `progressr` package.
 #' 
 #' @examples 
 #' if (requireNamespace("fable", quietly = TRUE) && requireNamespace("tsibbledata", quietly = TRUE)) {
@@ -42,6 +47,7 @@ model <- function(.data, ...){
 #' # Training a seasonal naive and ETS(A,A,A) model to the monthly 
 #' # "Food retailing" turnover for selected Australian states.
 #' library(dplyr)
+#' progressr::with_progress(
 #' aus_retail %>% 
 #'   filter(
 #'     Industry == "Food retailing",
@@ -51,6 +57,7 @@ model <- function(.data, ...){
 #'     snaive = SNAIVE(Turnover),
 #'     ets = ETS(log(Turnover) ~ error("A") + trend("A") + season("A")),
 #'   )
+#' )
 #' }
 #' 
 #' @export
diff --git a/man/model.Rd b/man/model.Rd
index ce12b159..8365fe4d 100644
--- a/man/model.Rd
+++ b/man/model.Rd
@@ -35,6 +35,14 @@ It is possible to estimate models in parallel using the
 according to that plan.
 }
 
+\section{Progress}{
+
+
+Progress on model estimation can be obtained by wrapping the code with
+\code{progressr::with_progress()}. Further customisation on how progress is
+reported can be controlled using the \code{progressr} package.
+}
+
 \examples{
 if (requireNamespace("fable", quietly = TRUE) && requireNamespace("tsibbledata", quietly = TRUE)) {
 library(fable)
@@ -47,6 +55,7 @@ aus_production \%>\%
 # Training a seasonal naive and ETS(A,A,A) model to the monthly 
 # "Food retailing" turnover for selected Australian states.
 library(dplyr)
+progressr::with_progress(
 aus_retail \%>\% 
   filter(
     Industry == "Food retailing",
@@ -56,6 +65,7 @@ aus_retail \%>\%
     snaive = SNAIVE(Turnover),
     ets = ETS(log(Turnover) ~ error("A") + trend("A") + season("A")),
   )
+)
 }
 
 }