From 32ad625e00aedae119373c33a91a79323c515bef Mon Sep 17 00:00:00 2001
From: almac2022 <al@newgraphenvironment.com>
Date: Mon, 16 Dec 2024 10:22:24 -0800
Subject: [PATCH] improve documentation to reference fpr_chk_dupes

---
 R/fpr_tidy_assign_site_id.R    | 12 ++++++++++--
 man/fpr_tidy_assign_site_id.Rd | 12 ++++++++++--
 2 files changed, 20 insertions(+), 4 deletions(-)

diff --git a/R/fpr_tidy_assign_site_id.R b/R/fpr_tidy_assign_site_id.R
index 38b3895..11613b5 100644
--- a/R/fpr_tidy_assign_site_id.R
+++ b/R/fpr_tidy_assign_site_id.R
@@ -1,8 +1,9 @@
 #' Function to process site ID value from pscis_crossing_id and my_crossing_reference
 #'
 #' Intended for processing field data from digital form in which only one value should be provided.
-#' It checks if the dataframe has both 'pscis_crossing_id' and 'my_crossing_reference' values, or none of them.
-#' If any rows violate these rules, it returns an error that prints out a simplified dataframe with violating rows.
+#' It checks to confirm the dataframe has one and only one of either a `pscis_crossing_id` or a `my_crossing_reference`.
+#' It also uses [fpr_chk_dupes()] to issue a warning if there are duplicate values of `pscis_crossing_id`,
+#' `my_crossing_reference` or `site_id`
 #'
 #' @param dat A dataframe to process. Default is NULL.
 #' @return A processed dataframe.
@@ -21,7 +22,14 @@
 #' date_time_start = Sys.time() + 0:3
 #' )
 #'
+#' #' dat_warn_dupe <- tibble(
+#' pscis_crossing_id = c(1, 3, NA, 4),
+#' my_crossing_reference = c(NA, NA, 3, NA),
+#' date_time_start = Sys.time() + 0:3
+#' )
+#'
 #' fpr_tidy_assign_site_id(dat_pass)
+#' fpr_tidy_assign_site_id(dat_warn_dupe)
 #' }
 fpr_tidy_assign_site_id <- function(dat = NULL) {
 
diff --git a/man/fpr_tidy_assign_site_id.Rd b/man/fpr_tidy_assign_site_id.Rd
index 9841ed3..4ebb7ee 100644
--- a/man/fpr_tidy_assign_site_id.Rd
+++ b/man/fpr_tidy_assign_site_id.Rd
@@ -14,8 +14,9 @@ A processed dataframe.
 }
 \description{
 Intended for processing field data from digital form in which only one value should be provided.
-It checks if the dataframe has both 'pscis_crossing_id' and 'my_crossing_reference' values, or none of them.
-If any rows violate these rules, it returns an error that prints out a simplified dataframe with violating rows.
+It checks to confirm the dataframe has one and only one of either a `pscis_crossing_id` or a `my_crossing_reference`.
+It also uses [fpr_chk_dupes()] to issue a warning if there are duplicate values of `pscis_crossing_id`,
+`my_crossing_reference` or `site_id`
 }
 \examples{
 \dontrun{
@@ -25,7 +26,14 @@ my_crossing_reference = c(NA, NA, 3, NA),
 date_time_start = Sys.time() + 0:3
 )
 
+#' dat_warn_dupe <- tibble(
+pscis_crossing_id = c(1, 3, NA, 4),
+my_crossing_reference = c(NA, NA, 3, NA),
+date_time_start = Sys.time() + 0:3
+)
+
 fpr_tidy_assign_site_id(dat_pass)
+fpr_tidy_assign_site_id(dat_warn_dupe)
 }
 }
 \concept{tidy}