REDCapCAST/R/read_redcap_tables.R

104 lines
3.1 KiB
R

#' 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.
#' @param uri REDCap database uri
#' @param token API token
#' @param records records to download
#' @param fields fields to download
#' @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 generics vector of auto-generated generic variable names to
#' ignore when discarding empty rows
#'
#' @return list of instruments
#' @importFrom REDCapR redcap_metadata_read redcap_read redcap_event_instruments
#' @include utils.r
#' @export
#'
#' @examples
#' # Examples will be provided later
read_redcap_tables <- function(uri,
token,
records = NULL,
fields = NULL,
events = NULL,
forms = NULL,
raw_or_label = "label",
split_forms = "all",
generics = c(
"record_id",
"redcap_event_name",
"redcap_repeat_instrument",
"redcap_repeat_instance"
)) {
if (!is.null(forms) | !is.null(events)){
arm_event_inst <- REDCapR::redcap_event_instruments(redcap_uri = uri,
token = token)
if (!is.null(forms)){
forms_test <- forms %in% unique(arm_event_inst$data$form)
if (any(!forms_test)){
stop("Not all supplied forms are valid")
}
}
if (!is.null(events)){
event_test <- events %in% unique(arm_event_inst$data$unique_event_name)
if (any(!forms_test)){
stop("Not all supplied event names are valid")
}
}
}
# Getting dataset
d <- REDCapR::redcap_read(
redcap_uri = uri,
token = token,
fields = fields,
events = events,
forms = forms,
records = records,
raw_or_label = raw_or_label
)[["data"]]
# Process repeat instrument naming
# Removes any extra characters other than a-z, 0-9 and "_", to mimic raw
# instrument names.
if ("redcap_repeat_instrument" %in% names(d)) {
d$redcap_repeat_instrument <- clean_redcap_name(d$redcap_repeat_instrument)
}
# Getting metadata
m <-
REDCapR::redcap_metadata_read (redcap_uri = uri, token = token)[["data"]]
# Processing metadata to reflect dataset
if (!is.null(c(fields,forms,events))){
m <- focused_metadata(m,names(d))
}
# Splitting
l <- REDCap_split(d,
m,
forms = split_forms,
primary_table_name = "")
# Sanitizing split list by removing completely empty rows apart from colnames
# in "generics"
sanitize_split(l,generics)
}