updated ui/ux

This commit is contained in:
Andreas Gammelgaard Damsbo 2025-03-24 14:40:30 +01:00
commit 16adb622ee
No known key found for this signature in database
10 changed files with 389 additions and 363 deletions

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@ -1 +1 @@
app_version <- function()'250320_1310'
app_version <- function()'250324_1432'

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@ -20,3 +20,55 @@ baseline_table <- function(data, fun.args = NULL, fun = gtsummary::tbl_summary,
return(out)
}
#' Create a baseline table
#'
#' @param data data
#' @param ... passed as fun.arg to baseline_table()
#' @param strat.var grouping/strat variable
#' @param add.p add comparison/p-value
#' @param add.overall add overall column
#'
#' @returns gtsummary table list object
#' @export
#'
#' @examples
#' mtcars |> create_baseline(by.var = "gear", add.p="yes"=="yes")
create_baseline <- function(data,...,by.var,add.p=FALSE,add.overall=FALSE){
if (by.var == "none" | !by.var %in% names(data)) {
by.var <- NULL
}
## These steps are to handle logicals/booleans, that messes up the order of columns
## Has been reported
if (!is.null(by.var)) {
if (identical("logical",class(data[[by.var]]))){
data[by.var] <- as.character(data[[by.var]])
}
}
out <- data |>
baseline_table(
fun.args =
list(
by = by.var,
...
)
)
if (!is.null(by.var)) {
if (isTRUE(add.overall)){
out <- out |> gtsummary::add_overall()
}
if (isTRUE(add.p)) {
out <- out |>
gtsummary::add_p() |>
gtsummary::bold_p()
}
}
out
}

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@ -302,6 +302,7 @@ data_visuals_server <- function(id,
{
tryCatch(
{
shiny::withProgress(message = "Drawing the plot. Hold tight for a moment..", {
rv$plot <- create_plot(
data = data(),
type = rv$plot.params()[["fun"]],
@ -309,6 +310,7 @@ data_visuals_server <- function(id,
y = input$secondary,
z = input$tertiary
)
})
},
# warning = function(warn) {
# showNotification(paste0(warn), type = "warning")

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@ -29,7 +29,7 @@ getfun <- function(x) {
#' @return output file name
#' @export
#'
write_quarto <- function(data,...) {
write_quarto <- function(data, ...) {
# Exports data to temporary location
#
# I assume this is more secure than putting it in the www folder and deleting
@ -50,7 +50,7 @@ write_quarto <- function(data,...) {
)
}
write_rmd <- function(data,...) {
write_rmd <- function(data, ...) {
# Exports data to temporary location
#
# I assume this is more secure than putting it in the www folder and deleting
@ -210,17 +210,17 @@ file_export <- function(data, output.format = c("df", "teal", "list"), filename,
#' default_parsing() |>
#' str()
default_parsing <- function(data) {
name_labels <- lapply(data,\(.x) REDCapCAST::get_attr(.x,attr = "label"))
name_labels <- lapply(data, \(.x) REDCapCAST::get_attr(.x, attr = "label"))
out <- data |>
REDCapCAST::parse_data() |>
REDCapCAST::as_factor() |>
REDCapCAST::numchar2fct(numeric.threshold = 8,character.throshold = 10) |>
REDCapCAST::numchar2fct(numeric.threshold = 8, character.throshold = 10) |>
REDCapCAST::as_logical() |>
REDCapCAST::fct_drop()
purrr::map2(out,name_labels,\(.x,.l){
if (!(is.na(.l) | .l=="")) {
purrr::map2(out, name_labels, \(.x, .l){
if (!(is.na(.l) | .l == "")) {
REDCapCAST::set_attr(.x, .l, attr = "label")
} else {
attr(x = .x, which = "label") <- NULL
@ -238,12 +238,14 @@ default_parsing <- function(data) {
#' @export
#'
#' @examples
#' ds <- mtcars |> lapply(\(.x) REDCapCAST::set_attr(.x,label=NA,attr = "label"))
#' ds |> remove_na_attr() |> str()
remove_na_attr <- function(data,attr="label"){
#' ds <- mtcars |> lapply(\(.x) REDCapCAST::set_attr(.x, label = NA, attr = "label"))
#' ds |>
#' remove_na_attr() |>
#' str()
remove_na_attr <- function(data, attr = "label") {
out <- data |> lapply(\(.x){
ls <- REDCapCAST::get_attr(data = .x,attr = attr)
if (is.na(ls) | ls == ""){
ls <- REDCapCAST::get_attr(data = .x, attr = attr)
if (is.na(ls) | ls == "") {
attr(x = .x, which = attr) <- NULL
}
.x
@ -261,10 +263,10 @@ remove_na_attr <- function(data,attr="label"){
#' @export
#'
#' @examples
#'data.frame(a=1:10,b=NA, c=c(2,NA)) |> remove_empty_cols(cutoff=.5)
remove_empty_cols <- function(data,cutoff=.7){
filter <- apply(X = data,MARGIN = 2,FUN = \(.x){
sum(as.numeric(!is.na(.x)))/length(.x)
#' data.frame(a = 1:10, b = NA, c = c(2, NA)) |> remove_empty_cols(cutoff = .5)
remove_empty_cols <- function(data, cutoff = .7) {
filter <- apply(X = data, MARGIN = 2, FUN = \(.x){
sum(as.numeric(!is.na(.x))) / length(.x)
}) >= cutoff
data[filter]
}
@ -280,18 +282,18 @@ remove_empty_cols <- function(data,cutoff=.7){
#' @export
#'
#' @examples
#' ls_d <- list(test=c(1:20))
#' ls_d <- list(test = c(1:20))
#' ls_d <- list()
#' data.frame(letters[1:20],1:20) |> append_list(ls_d,"letters")
#' letters[1:20]|> append_list(ls_d,"letters")
append_list <- function(data,list,index){
#' data.frame(letters[1:20], 1:20) |> append_list(ls_d, "letters")
#' letters[1:20] |> append_list(ls_d, "letters")
append_list <- function(data, list, index) {
## This will overwrite and not warn
## Not very safe, but convenient to append code to list
if (index %in% names(list)){
if (index %in% names(list)) {
list[[index]] <- data
out <- list
} else {
out <- setNames(c(list,list(data)),c(names(list),index))
out <- setNames(c(list, list(data)), c(names(list), index))
}
out
}
@ -305,7 +307,33 @@ append_list <- function(data,list,index){
#' @export
#'
#' @examples
#' c(NA,1:10,rep(NA,3)) |> missing_fraction()
missing_fraction <- function(data){
NROW(data[is.na(data)])/NROW(data)
#' c(NA, 1:10, rep(NA, 3)) |> missing_fraction()
missing_fraction <- function(data) {
NROW(data[is.na(data)]) / NROW(data)
}
#' Ultra short data dascription
#'
#' @param data
#'
#' @returns character vector
#' @export
#'
#' @examples
#' data.frame(
#' sample(1:8, 20, TRUE),
#' sample(c(1:8, NA), 20, TRUE)
#' ) |> data_description()
data_description <- function(data) {
data <- if (shiny::is.reactive(data)) data() else data
sprintf(
i18n("Data has %s observations and %s variables, with %s (%s%%) complete cases"),
nrow(data),
ncol(data),
sum(complete.cases(data)),
signif(100 * (1 - missing_fraction(data)), 3)
)
}

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@ -43,15 +43,16 @@ plot.tbl_regression <- function(x,
# Removes redundant label
df_coefs$label[df_coefs$row_type == "label"] <- ""
# browser()
# Add estimate value to reference level
if (plot_ref == TRUE){
df_coefs[df_coefs$var_type == "categorical" & is.na(df_coefs$reference_row),"estimate"] <- if (x$inputs$exponentiate) 1 else 0}
if (plot_ref == TRUE) {
df_coefs[df_coefs$var_type %in% c("categorical", "dichotomous") & df_coefs$reference_row & !is.na(df_coefs$reference_row), "estimate"] <- if (x$inputs$exponentiate) 1 else 0
}
p <- df_coefs |>
ggstats::ggcoef_plot(exponentiate = x$inputs$exponentiate, ...)
if (x$inputs$exponentiate){
if (x$inputs$exponentiate) {
p <- symmetrical_scale_x_log10(p)
}
p
@ -89,7 +90,8 @@ merge_long <- function(list, model.names) {
)
setNames(d, gsub("_[0-9]{,}$", "", names(d)))
}) |>
dplyr::bind_rows() |> dplyr::mutate(model=as_factor(model))
dplyr::bind_rows() |>
dplyr::mutate(model = as_factor(model))
l_merged$table_body <- df_body_long
@ -109,12 +111,25 @@ merge_long <- function(list, model.names) {
#' @export
#'
#' @examples
#' limit_log(-.1,floor)
#' limit_log(.1,ceiling)
#' limit_log(-2.1,ceiling)
#' limit_log(2.1,ceiling)
limit_log <- function(data,fun,...){
fun(10^-floor(data)*10^data)/10^-floor(data)
#' limit_log(-.1, floor)
#' limit_log(.1, ceiling)
#' limit_log(-2.1, ceiling)
#' limit_log(2.1, ceiling)
limit_log <- function(data, fun, ...) {
fun(10^-floor(data) * 10^data) / 10^-floor(data)
}
#' Create summetric log ticks
#'
#' @param data numeric vector
#'
#' @returns
#' @export
#'
#' @examples
#' c(sample(seq(.1, 1, .1), 3), sample(1:10, 3)) |> create_log_tics()
create_log_tics <- function(data) {
sort(round(unique(c(1 / data, data, 1)), 2))
}
#' Ensure symmetrical plot around 1 on a logarithmic x scale for ratio plots
@ -126,18 +141,18 @@ limit_log <- function(data,fun,...){
#' @returns ggplot2 object
#' @export
#'
symmetrical_scale_x_log10 <- function(plot,breaks=c(1,2,3,5,10),...){
symmetrical_scale_x_log10 <- function(plot, breaks = c(1, 2, 3, 5, 10), ...) {
rx <- ggplot2::layer_scales(plot)$x$get_limits()
x_min <- floor(10*rx[1])/10
x_max <- ceiling(10*rx[2])/10
x_min <- floor(10 * rx[1]) / 10
x_max <- ceiling(10 * rx[2]) / 10
rx_min <- limit_log(rx[1],floor)
rx_max <- limit_log(rx[2],ceiling)
rx_min <- limit_log(rx[1], floor)
rx_max <- limit_log(rx[2], ceiling)
max_abs_x <- max(abs(c(x_min,x_max)))
max_abs_x <- max(abs(c(x_min, x_max)))
ticks <- log10(breaks)+(ceiling(max_abs_x)-1)
ticks <- log10(breaks) + (ceiling(max_abs_x) - 1)
plot + ggplot2::scale_x_log10(limits=c(rx_min,rx_max),breaks=create_log_tics(10^ticks[ticks<=max_abs_x]))
plot + ggplot2::scale_x_log10(limits = c(rx_min, rx_max), breaks = create_log_tics(10^ticks[ticks <= max_abs_x]))
}

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@ -119,8 +119,8 @@ regression_table_create <- function(x, ..., args.list = NULL, fun = "gtsummary::
}
out <- do.call(getfun(fun), c(list(x = x), args.list))
out |>
gtsummary::add_glance_source_note() # |>
out #|>
# gtsummary::add_glance_source_note() # |>
# gtsummary::bold_p()
}