gp with CRAN in sight

R/REDCap_split.r

@@ -48,15 +48,16 @@
 #' records <- read.csv("/path/to/data/ExampleProject_DATA_2018-06-03_1700.csv")
 #'
 #' # Get the metadata
-#' metadata <- read.csv("/path/to/data/ExampleProject_DataDictionary_2018-06-03.csv")
+#' metadata <- read.csv(
+#' "/path/to/data/ExampleProject_DataDictionary_2018-06-03.csv")
 #'
 #' # Split the tables
 #' REDCapRITS::REDCap_split(records, metadata)
 #'
 #' # In conjunction with the R export script ---------------------------------
 #'
-#' # You must set the working directory first since the REDCap data export script
-#' # contains relative file references.
+#' # You must set the working directory first since the REDCap data export
+#' # script contains relative file references.
 #' setwd("/path/to/data/")
 #'
 #' # Run the data export script supplied by REDCap.
@@ -148,7 +149,8 @@ REDCap_split <- function(records,
 
     if (forms == "repeating" && primary_table_name %in% subtables) {
       warning(
-        "The label given to the primary table is already used by a repeating instrument. The primary table label will be left blank."
+        "The label given to the primary table is already used by a repeating
+        instrument. The primary table label will be left blank."
       )
       primary_table_name <- ""
     } else if (primary_table_name > "") {
@@ -159,7 +161,8 @@ REDCap_split <- function(records,
     for (i in names(out)) {
       if (i == primary_table_name) {
         out_fields <- which(vars_in_data %in% c(universal_fields,
-                                                fields[!fields[, 2] %in% subtables, 1]))
+                                                fields[!fields[, 2] %in%
+                                                         subtables, 1]))
         out[[primary_table_index]] <-
           out[[primary_table_index]][out_fields]
 

R/read_redcap_tables.R

@@ -1,10 +1,9 @@
 #' Download REDCap data
 #'
 #' Implementation of REDCap_split with a focused data acquisition approach using
-#' REDCapR::redcap_read nad only downloading specified fields, forms and/or events
-#' using the built-in focused_metadata
-#' including some clean-up. Works with longitudinal projects with repeating
-#' instruments.
+#' REDCapR::redcap_read nad only downloading specified fields, forms and/or
+#' events using the built-in focused_metadata including some clean-up.
+#' Works with longitudinal projects with repeating instruments.
 #' @param uri REDCap database uri
 #' @param token API token
 #' @param records records to download
@@ -12,7 +11,8 @@
 #' @param events events to download
 #' @param forms forms to download
 #' @param raw_or_label raw or label tags
-#' @param split_forms Whether to split "repeating" or "all" forms, default is all.
+#' @param split_forms Whether to split "repeating" or "all" forms, default is
+#' all.
 #' @param generics vector of auto-generated generic variable names to
 #' ignore when discarding empty rows
 #'
@@ -73,7 +73,8 @@ read_redcap_tables <- function(uri,
   )[["data"]]
 
   # Process repeat instrument naming
-  # Removes any extra characters other than a-z, 0-9 and "_", to mimic raw instrument names.
+  # Removes any extra characters other than a-z, 0-9 and "_", to mimic raw
+  # instrument names.
   if ("redcap_repeat_instrument" %in% names(d)) {
     d$redcap_repeat_instrument <-
     gsub("[^a-z0-9_]", "", gsub(" ", "_", tolower(d$redcap_repeat_instrument)))

R/redcap_wider.R

@@ -27,7 +27,8 @@ redcap_wider <-
            inst.glue = "{.value}_{redcap_repeat_instance}") {
     all_names <- unique(do.call(c, lapply(list, names)))
 
-    if (!any(c("redcap_event_name", "redcap_repeat_instrument") %in% all_names)) {
+    if (!any(c("redcap_event_name", "redcap_repeat_instrument") %in%
+             all_names)) {
       stop(
         "The dataset does not include a 'redcap_event_name' variable.
          redcap_wider only handles projects with repeating instruments or
@@ -35,11 +36,6 @@ redcap_wider <-
       )
     }
 
-    # if (any(grepl("_timestamp",all_names))){
-    #   stop("The dataset includes a '_timestamp' variable, which is not supported
-    #        by this function yet. Sorry! Feel free to contribute :)")
-    # }
-
     id.name <- all_names[1]
 
     l <- lapply(list, function(i) {

R/utils.r

@@ -138,7 +138,8 @@ match_fields_to_form <- function(metadata, vars_in_data) {
   names(fields) <- c("field_name", "form_name")
 
   # Process instrument status fields
-  form_names <- unique(metadata[,grepl(".*[Ff]orm[._][Nn]ame$",names(metadata))])
+  form_names <- unique(metadata[,grepl(".*[Ff]orm[._][Nn]ame$",
+                                       names(metadata))])
   form_complete_fields <- data.frame(
     field_name = paste0(form_names, "_complete"),
     form_name = form_names,