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Author SHA1 Message Date
085aa9de62 new workflow 2023-07-04 16:58:12 +02:00
e0c1767c9a resetting page publishing 2023-07-04 16:57:25 +02:00
66bd7cb67d deleted 2023-07-04 16:09:39 +02:00
64410c910d new version submitted to CRAN 2023-07-04 16:09:07 +02:00
cdb3375f6a new comments 2023-07-04 16:06:21 +02:00
8bd4d9ade7 three new functions and new version 2023-07-04 16:03:24 +02:00
12 changed files with 384 additions and 40 deletions

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@ -1,3 +0,0 @@
Version: 23.6.1
Date: 2023-06-05 06:44:45 UTC
SHA: f2d5b8f6007b7f953c525e58e8b47ec8d702d9be

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@ -1,6 +1,6 @@
Package: REDCapCAST
Title: REDCap Castellated Data Handling
Version: 23.6.1
Version: 23.6.2
Authors@R: c(
person("Andreas Gammelgaard", "Damsbo", email = "agdamsbo@clin.au.dk", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-7559-1154")),
@ -48,6 +48,7 @@ Collate:
'utils.r'
'process_user_input.r'
'REDCap_split.r'
'ds2dd.R'
'read_redcap_tables.R'
'redcap_wider.R'
'redcapcast_data.R'

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@ -2,12 +2,15 @@
export(REDCap_split)
export(clean_redcap_name)
export(d2w)
export(ds2dd)
export(focused_metadata)
export(match_fields_to_form)
export(read_redcap_tables)
export(redcap_wider)
export(sanitize_split)
export(split_non_repeating_forms)
export(strsplitx)
importFrom(REDCapR,redcap_event_instruments)
importFrom(REDCapR,redcap_metadata_read)
importFrom(REDCapR,redcap_read)

13
NEWS.md
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@ -1,3 +1,16 @@
# REDCapCAST 23.6.2
This version marks the introduction of a few helper functions to handle database creation.
### Functions
* New: `ds2dd()` function migrating from the `stRoke`-package. Assists in building a data dictionary for REDCap from a dataset.
* New: `strsplitx()` function to ease the string splitting as an extension of `base::strsplit()`. Inspiration from https://stackoverflow.com/a/11014253/21019325 and https://www.r-bloggers.com/2018/04/strsplit-but-keeping-the-delimiter/.
* New: `d2n()` function converts single digits to written numbers. Used to sanitize variable and form names in REDCap database creation. For more universal number to word I would suggest `english::word()` or `xfun::numbers_to_words()`, though I have not been testing these.
# REDCapCAST 23.6.1
### Documentation:

84
R/ds2dd.R Normal file
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@ -0,0 +1,84 @@
utils::globalVariables(c("redcapcast_meta"))
#' Data set to data dictionary function
#'
#' Migrated from stRoke ds2dd(). Fits better with the functionality of
#' 'REDCapCAST'
#' @param ds data set
#' @param record.id name or column number of id variable, moved to first row of
#' data dictionary, character of integer. Default is "record_id".
#' @param form.name vector of form names, character string, length 1 or length
#' equal to number of variables. Default is "basis".
#' @param field.type vector of field types, character string, length 1 or length
#' equal to number of variables. Default is "text.
#' @param field.label vector of form names, character string, length 1 or length
#' equal to number of variables. Default is NULL and is then identical to field
#' names.
#' @param include.column.names Flag to give detailed output including new
#' column names for original data set for upload.
#' @param metadata Metadata column names. Default is the included
#' REDCapCAST::redcapcast_data.
#'
#' @return data.frame or list of data.frame and vector
#' @export
#'
#' @examples
#' redcapcast_data$record_id <- seq_len(nrow(redcapcast_data))
#' ds2dd(redcapcast_data, include.column.names=TRUE)
ds2dd <-
function(ds,
record.id = "record_id",
form.name = "basis",
field.type = "text",
field.label = NULL,
include.column.names = FALSE,
metadata = names(redcapcast_meta)) {
dd <- data.frame(matrix(ncol = length(metadata), nrow = ncol(ds)))
colnames(dd) <- metadata
if (is.character(record.id) & !record.id %in% colnames(ds)) {
stop("Provided record.id is not a variable name in provided data set.")
}
# renaming to lower case and substitute spaces with underscore
field.name <- gsub(" ", "_", tolower(colnames(ds)))
# handles both character and integer
colsel <-
colnames(ds) == colnames(ds[record.id])
if (summary(colsel)[3] != 1) {
stop("Provided record.id has to be or refer to a uniquely named column.")
}
dd[, "field_name"] <-
c(field.name[colsel], field.name[!colsel])
if (length(form.name) > 1 & length(form.name) != ncol(ds)) {
stop(
"Provided form.name should be of length 1 (value is reused) or equal
length as number of variables in data set."
)
}
dd[, "form_name"] <- form.name
if (length(field.type) > 1 & length(field.type) != ncol(ds)) {
stop(
"Provided field.type should be of length 1 (value is reused) or equal
length as number of variables in data set."
)
}
dd[, "field_type"] <- field.type
if (is.null(field.label)) {
dd[, "field_label"] <- dd[, "field_name"]
} else
dd[, "field_label"] <- field.label
if (include.column.names){
list("DataDictionary"=dd,"Column names"=field.name)
} else dd
}

138
R/utils.r
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@ -276,3 +276,141 @@ split_non_repeating_forms <-
structure(x, names = forms)
}
#' Extended string splitting
#'
#' Can be used as a substitute of the base function. Main claim to fame is
#' easing the split around the defined delimiter, see example.
#' @param x data
#' @param split delimiter
#' @param type Split type. Can be c("classic", "before", "after", "around")
#' @param perl perl param from strsplit()
#' @param ... additional parameters are passed to base strsplit handling splits
#'
#' @return list
#' @export
#'
#' @examples
#' test <- c("12 months follow-up", "3 steps", "mRS 6 weeks", "Counting to 231 now")
#' strsplitx(test,"[0-9]",type="around")
strsplitx <- function(x,
split,
type = "classic",
perl = FALSE,
...) {
if (type == "classic") {
# use base::strsplit
out <- base::strsplit(x = x, split = split, perl = perl, ...)
} else if (type == "before") {
# split before the delimiter and keep it
out <- base::strsplit(x = x,
split = paste0("(?<=.)(?=", split, ")"),
perl = TRUE,
...)
} else if (type == "after") {
# split after the delimiter and keep it
out <- base::strsplit(x = x,
split = paste0("(?<=", split, ")"),
perl = TRUE,
...)
} else if (type == "around") {
# split around the defined delimiter
out <- base::strsplit(gsub("~~", "~", # Removes double ~
gsub("^~", "", # Removes leading ~
gsub(
# Splits and inserts ~ at all delimiters
paste0("(", split, ")"), "~\\1~", x
))), "~")
} else {
# wrong type input
stop("type must be 'classic', 'after', 'before' or 'around'!")
}
out
}
#' Convert single digits to words
#'
#' @param x data. Handle vectors, data.frames and lists
#' @param lang language. Danish (da) and English (en), Default is "en"
#' @param neutrum for numbers depending on counted word
#' @param everything flag to also split numbers >9 to single digits
#'
#' @return returns characters in same format as input
#' @export
#'
#' @examples
#' d2w(c(2:8,21))
#' d2w(data.frame(2:7,3:8,1),lang="da",neutrum=TRUE)
#'
#' ## If everything=T, also larger numbers are reduced.
#' ## Elements in the list are same length as input
#' d2w(list(2:8,c(2,6,4,23),2), everything=TRUE)
#'
d2w <- function(x, lang = "en", neutrum=FALSE, everything=FALSE) {
# In Danish the written 1 depends on the counted word
if (neutrum) nt <- "t" else nt <- "n"
# A sapply() call with nested lapply() to handle vectors, data.frames and lists
convert <- function(x, lang, neutrum) {
zero_nine = data.frame(
num = 0:9,
en = c(
'zero',
'one',
'two',
'three',
'four',
'five',
'six',
'seven',
'eight',
'nine'
),
da = c(
"nul",
paste0("e",nt),
"to",
"tre",
"fire",
"fem",
"seks",
"syv",
"otte",
"ni"
)
)
wrd <- lapply(x, function(i) {
zero_nine[, tolower(lang)][zero_nine[, 1] == i]
})
sub <- lengths(wrd) == 1
x[sub] <- wrd[sub]
unlist(x)
}
# Also converts numbers >9 to single digits and writes out
# Uses strsplitx()
if (everything) {
out <- sapply(x,function(y){
do.call(c,lapply(y,function(z){
v <- strsplitx(z,"[0-9]",type="around")
Reduce(paste,sapply(v,convert,lang = lang, neutrum = neutrum))
}))
})
} else {
out <- sapply(x,convert,lang = lang, neutrum = neutrum)
}
if (is.data.frame(x)) out <- data.frame(out)
out
}

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@ -1,54 +1,22 @@
results$cran_summary()
For a CRAN submission we recommend that you fix all NOTEs, WARNINGs and ERRORs.
## Test environments
- R-hub windows-x86_64-devel (r-devel)
- R-hub ubuntu-gcc-release (r-release)
- R-hub fedora-clang-devel (r-devel)
## R CMD check results
On windows-x86_64-devel (r-devel)
checking CRAN incoming feasibility ... [17s] NOTE
Maintainer: 'Andreas Gammelgaard Damsbo <agdamsbo@clin.au.dk>'
New submission
Possibly misspelled words in DESCRIPTION:
Egeler (8:45)
REDCap (2:8, 10:39, 11:30, 14:5)
REDCapRITS (8:26)
interoperability (19:44)
On windows-x86_64-devel (r-devel)
checking for non-standard things in the check directory ... NOTE
Found the following files/directories:
''NULL''
On windows-x86_64-devel (r-devel)
checking for detritus in the temp directory ... NOTE
Found the following files/directories:
'lastMiKTeXException'
On ubuntu-gcc-release (r-release)
checking CRAN incoming feasibility ... [6s/24s] NOTE
Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@clin.au.dk>
New submission
Possibly misspelled words in DESCRIPTION:
Egeler (8:45)
REDCap (2:8, 10:39, 11:30, 14:5)
REDCapRITS (8:26)
On ubuntu-gcc-release (r-release), fedora-clang-devel (r-devel)
checking HTML version of manual ... NOTE
Skipping checking HTML validation: no command 'tidy' found
On fedora-clang-devel (r-devel)
checking CRAN incoming feasibility ... [7s/21s] NOTE
Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@clin.au.dk>
New submission
Possibly misspelled words in DESCRIPTION:
Egeler (8:45)
REDCap (2:8, 10:39, 11:30, 14:5)
REDCapRITS (8:26)
0 errors ✔ | 0 warnings ✔ | 6 notes ✖
0 errors ✔ | 0 warnings ✔ | 3 notes ✖

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@ -1,11 +1,13 @@
Assesment
CMD
Codecov
DOI
DataDictionary
GStat
GithubActions
JSON
Lifecycle
METACRAN
Pivotting
README
REDCap
@ -14,11 +16,13 @@ REDCapRITS
SpectrumHealthResearch
al
api
da
demonstrational
descirption
desireable
doi
dplyr
ds
et
immprovements
jbi
@ -27,6 +31,11 @@ matadata
md
nad
og
param
perl
redcapcast
stRoke
strsplit
thorugh
tidyverse
uri

32
man/d2w.Rd Normal file
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@ -0,0 +1,32 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils.r
\name{d2w}
\alias{d2w}
\title{Convert single digits to words}
\usage{
d2w(x, lang = "en", neutrum = FALSE, everything = FALSE)
}
\arguments{
\item{x}{data. Handle vectors, data.frames and lists}
\item{lang}{language. Danish (da) and English (en), Default is "en"}
\item{neutrum}{for numbers depending on counted word}
\item{everything}{flag to also split numbers >9 to single digits}
}
\value{
returns characters in same format as input
}
\description{
Convert single digits to words
}
\examples{
d2w(c(2:8,21))
d2w(data.frame(2:7,3:8,1),lang="da",neutrum=TRUE)
## If everything=T, also larger numbers are reduced.
## Elements in the list are same length as input
d2w(list(2:8,c(2,6,4,23),2), everything=TRUE)
}

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man/ds2dd.Rd Normal file
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@ -0,0 +1,49 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ds2dd.R
\name{ds2dd}
\alias{ds2dd}
\title{Data set to data dictionary function}
\usage{
ds2dd(
ds,
record.id = "record_id",
form.name = "basis",
field.type = "text",
field.label = NULL,
include.column.names = FALSE,
metadata = names(redcapcast_meta)
)
}
\arguments{
\item{ds}{data set}
\item{record.id}{name or column number of id variable, moved to first row of
data dictionary, character of integer. Default is "record_id".}
\item{form.name}{vector of form names, character string, length 1 or length
equal to number of variables. Default is "basis".}
\item{field.type}{vector of field types, character string, length 1 or length
equal to number of variables. Default is "text.}
\item{field.label}{vector of form names, character string, length 1 or length
equal to number of variables. Default is NULL and is then identical to field
names.}
\item{include.column.names}{Flag to give detailed output including new
column names for original data set for upload.}
\item{metadata}{Metadata column names. Default is the included
REDCapCAST::redcapcast_data.}
}
\value{
data.frame or list of data.frame and vector
}
\description{
Migrated from stRoke ds2dd(). Fits better with the functionality of
'REDCapCAST'
}
\examples{
redcapcast_data$record_id <- seq_len(nrow(redcapcast_data))
ds2dd(redcapcast_data, include.column.names=TRUE)
}

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man/strsplitx.Rd Normal file
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@ -0,0 +1,30 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils.r
\name{strsplitx}
\alias{strsplitx}
\title{Extended string splitting}
\usage{
strsplitx(x, split, type = "classic", perl = FALSE, ...)
}
\arguments{
\item{x}{data}
\item{split}{delimiter}
\item{type}{Split type. Can be c("classic", "before", "after", "around")}
\item{perl}{perl param from strsplit()}
\item{...}{additional parameters are passed to base strsplit handling splits}
}
\value{
list
}
\description{
Can be used as a substitute of the base function. Main claim to fame is
easing the split around the defined delimiter, see example.
}
\examples{
test <- c("12 months follow-up", "3 steps", "mRS 6 weeks", "Counting to 231 now")
strsplitx(test,"[0-9]",type="around")
}

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@ -0,0 +1,20 @@
test_that("strsplitx works", {
expect_equal(2 * 2, 4)
test <- c("12 months follow-up", "3 steps", "mRS 6 weeks", "Counting to 231 now")
expect_length(strsplitx(test,"[0-9]",type="around")[[1]],3)
expect_equal(strsplitx(test,"[0-9]",type="classic")[[2]][1],"")
expect_length(strsplitx(test,"[0-9]",type="classic")[[4]],4)
expect_length(strsplitx(test,"[0-9]",type="classic")[[4]],4)
})
test_that("d2w works", {
expect_length(d2w(c(2:8,21)),8)
expect_equal(d2w(data.frame(2:7,3:8,1),lang="da",
neutrum=TRUE)[1,3],"et")
expect_equal(d2w(list(2:8,c(2,6,4,23),2), everything=T)[[2]][4],"two three")
})