new version inbound

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Andreas Gammelgaard Damsbo 2025-10-02 11:19:19 +02:00
parent 0e0df73744
commit 02fd53a352
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8 changed files with 1130 additions and 310 deletions

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@ -1,6 +1,6 @@
Package: FreesearchR
Title: Easy data analysis for clinicians
Version: 25.9.3
Version: 25.10.1
Authors@R: c(
person("Andreas Gammelgaard", "Damsbo",email="agdamsbo@clin.au.dk", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-7559-1154")),

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@ -1,9 +1,11 @@
# FreesearchR 25.9.3 -DEV
# FreesearchR 25.10.1
*NEW* Improvements to translations with more strings having been translated.
*NEW* Sample data has been filtered to only include a few select packages (NHANES and stRoke).
*NEW* Missings evaluations slightly tweaked to include bold significant p-values for easier overview.
# FreesearchR 25.9.2
*NEW* Improvements to translations with more strings having been translated.

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@ -1 +1 @@
app_version <- function()'25.9.3'
app_version <- function()'25.10.1'

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@ -1 +1 @@
hosted_version <- function()'v25.9.3-251002'
hosted_version <- function()'v25.10.1-251002'

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@ -1,7 +1,7 @@
########
#### Current file: /var/folders/9l/xbc19wxx0g79jdd2sf_0v291mhwh7f/T//Rtmpo2rU34/file15cb36d55cf55.R
#### Current file: /var/folders/9l/xbc19wxx0g79jdd2sf_0v291mhwh7f/T//RtmpWiu9wh/file1e994fcc5757.R
########
i18n_path <- here::here("translations")
@ -62,7 +62,7 @@ i18n$set_translation_language("en")
#### Current file: /Users/au301842/FreesearchR/R//app_version.R
########
app_version <- function()'25.9.2'
app_version <- function()'25.10.1'
########
@ -3433,7 +3433,8 @@ dummy_Imports <- function() {
parameters::ci(),
DT::addRow(),
bslib::accordion(),
NHANES::NHANES()
NHANES::NHANES(),
stRoke::add_padding()
)
# https://github.com/hadley/r-pkgs/issues/828
}
@ -3948,12 +3949,93 @@ simple_snake <- function(data){
gsub("[\\s+]","_",gsub("[^\\w\\s:-]", "", tolower(data), perl=TRUE), perl=TRUE)
}
#' Data type assessment.
#'
#' @description
#' These are more overall than the native typeof. This is used to assess a more
#' meaningful "clinical" data type.
#'
#' @param data vector or data.frame. if data frame, each column is evaluated.
#'
#' @returns outcome type
#' @export
#'
#' @examples
#' mtcars |>
#' default_parsing() |>
#' lapply(data_type)
#' mtcars |>
#' default_parsing() |>
#' data_type()
#' c(1, 2) |> data_type()
#' 1 |> data_type()
#' c(rep(NA, 10)) |> data_type()
#' sample(1:100, 50) |> data_type()
#' factor(letters[1:20]) |> data_type()
#' as.Date(1:20) |> data_type()
data_type <- function(data) {
if (is.data.frame(data)) {
sapply(data, data_type)
} else {
cl_d <- class(data)
l_unique <- length(unique(na.omit(data)))
if (all(is.na(data))) {
out <- "empty"
} else if (l_unique < 2) {
out <- "monotone"
} else if (any(c("factor", "logical") %in% cl_d) | l_unique == 2) {
if (identical("logical", cl_d) | l_unique == 2) {
out <- "dichotomous"
} else {
# if (is.ordered(data)) {
# out <- "ordinal"
# } else {
out <- "categorical"
# }
}
} else if (identical(cl_d, "character")) {
out <- "text"
} else if (any(c("hms", "Date", "POSIXct", "POSIXt") %in% cl_d)) {
out <- "datetime"
} else if (l_unique > 2) {
## Previously had all thinkable classes
## Now just assumes the class has not been defined above
## any(c("numeric", "integer", "hms", "Date", "timediff") %in% cl_d) &
out <- "continuous"
} else {
out <- "unknown"
}
out
}
}
#' Recognised data types from data_type
#'
#' @returns vector
#' @export
#'
#' @examples
#' data_types()
data_types <- function() {
list(
"empty" = list(descr="Variable of all NAs",classes="Any class"),
"monotone" = list(descr="Variable with only one unique value",classes="Any class"),
"dichotomous" = list(descr="Variable with only two unique values",classes="Any class"),
"categorical"= list(descr="Factor variable",classes="factor (ordered or unordered)"),
"text"= list(descr="Character variable",classes="character"),
"datetime"= list(descr="Variable of time, date or datetime values",classes="hms, Date, POSIXct and POSIXt"),
"continuous"= list(descr="Numeric variable",classes="numeric, integer or double"),
"unknown"= list(descr="Anything not falling within the previous",classes="Any other class")
)
}
########
#### Current file: /Users/au301842/FreesearchR/R//hosted_version.R
########
hosted_version <- function()'v25.9.2-250925'
hosted_version <- function()'v25.10.1-251002'
########
@ -3966,11 +4048,375 @@ html_dependency_FreesearchR <- function() {
version = packageVersion("FreesearchR"),
src = list(href = "FreesearchR", file = "assets"),
package = "FreesearchR",
script = "js/FreesearchR.js",
stylesheet = "css/FreesearchR.css"
)
}
########
#### Current file: /Users/au301842/FreesearchR/R//import_globalenv-ext.R
########
#' @title Import data from an Environment
#'
#' @description Let the user select a dataset from its own environment or from a package's environment.
#' Modified from datamods
#'
#' @param id Module's ID.
#' @param globalenv Search for data in Global environment.
#' @param packages Name of packages in which to search data.
#' @param title Module's title, if `TRUE` use the default title,
#' use `NULL` for no title or a `shiny.tag` for a custom one.
#'
#' @export
#'
#' @name import-globalenv
#'
import_globalenv_ui <- function(id,
globalenv = TRUE,
packages = datamods::get_data_packages(),
title = TRUE) {
ns <- NS(id)
choices <- list()
if (isTRUE(globalenv)) {
choices <- append(choices, "Global Environment")
}
if (!is.null(packages)) {
choices <- append(choices, list(Packages = as.character(packages)))
}
if (isTRUE(globalenv)) {
selected <- "Global Environment"
} else {
selected <- packages[1]
}
if (isTRUE(title)) {
title <- tags$h4(
i18n$t("Import a dataset from an environment"),
class = "datamods-title"
)
}
tags$div(
class = "datamods-import",
datamods:::html_dependency_datamods(),
title,
shinyWidgets::pickerInput(
inputId = ns("env"),
label = i18n$t("Select a data source:"),
choices = choices,
selected = selected,
width = "100%",
options = list(
"title" = i18n$t("Select source"),
"live-search" = TRUE,
"size" = 10
)
),
shinyWidgets::pickerInput(
inputId = ns("data"),
label = i18n$t("Select a dataset:"),
# selected = character(0),
choices = NULL,
# options = list(title = i18n$t("List of datasets...")),
width = "100%"
),
tags$div(
id = ns("import-placeholder"),
shinyWidgets::alert(
id = ns("import-result"),
status = "info",
tags$b(i18n$t("No data selected!")),
i18n$t("Use a datasat from your environment or from the environment of a package."),
dismissible = TRUE
)
),
uiOutput(
outputId = ns("container_valid_btn"),
style = "margin-top: 20px;"
)
)
}
#' @param btn_show_data Display or not a button to display data in a modal window if import is successful.
#' @param show_data_in Where to display data: in a `"popup"` or in a `"modal"` window.
#' @param trigger_return When to update selected data:
#' `"button"` (when user click on button) or
#' `"change"` (each time user select a dataset in the list).
#' @param return_class Class of returned data: `data.frame`, `data.table`, `tbl_df` (tibble) or `raw`.
#' @param reset A `reactive` function that when triggered resets the data.
#'
#' @export
#'
#' @importFrom shiny moduleServer reactiveValues observeEvent reactive removeUI is.reactive icon actionLink isTruthy
#' @importFrom htmltools tags tagList
#' @importFrom shinyWidgets updatePickerInput
#'
#' @rdname import-globalenv
import_globalenv_server <- function(id,
btn_show_data = TRUE,
show_data_in = c("popup", "modal"),
trigger_return = c("button", "change"),
return_class = c("data.frame", "data.table", "tbl_df", "raw"),
reset = reactive(NULL)) {
trigger_return <- match.arg(trigger_return)
return_class <- match.arg(return_class)
module <- function(input, output, session) {
ns <- session$ns
imported_rv <- reactiveValues(data = NULL, name = NULL)
temporary_rv <- reactiveValues(data = NULL, name = NULL, status = NULL)
observeEvent(reset(), {
temporary_rv$data <- NULL
temporary_rv$name <- NULL
temporary_rv$status <- NULL
})
output$container_valid_btn <- renderUI({
if (identical(trigger_return, "button")) {
button_import()
}
})
observeEvent(input$env, {
if (identical(input$env, "Global Environment")) {
choices <- datamods:::search_obj("data.frame")
} else {
choices <- datamods:::list_pkg_data(input$env)
}
if (is.null(choices)) {
choices <- i18n$t("No dataset here...")
choicesOpt <- list(disabled = TRUE)
} else {
choicesOpt <- list(
subtext = datamods:::get_dimensions(choices)
)
}
temporary_rv$package <- attr(choices, "package")
shinyWidgets::updatePickerInput(
session = session,
inputId = "data",
selected = character(0),
choices = choices,
choicesOpt = choicesOpt,
options = list(title = i18n$t("List of datasets..."))
)
})
observe(
shinyWidgets::alert(
id = "import-result",
status = "info",
tags$b(i18n$t("No data selected!")),
i18n$t("Use a datasat from your environment or from the environment of a package."),
dismissible = TRUE
)
)
observeEvent(input$trigger, {
if (identical(trigger_return, "change")) {
datamods:::hideUI(selector = paste0("#", ns("container_valid_btn")))
}
})
observeEvent(input$data, {
if (!isTruthy(input$data)) {
datamods:::toggle_widget(inputId = "confirm", enable = FALSE)
datamods:::insert_alert(
selector = ns("import"),
status = "info",
tags$b(i18n$t("No data selected!")),
i18n$t("Use a dataset from your environment or from the environment of a package.")
)
} else {
name_df <- input$data
if (!is.null(temporary_rv$package)) {
attr(name_df, "package") <- temporary_rv$package
}
imported <- try(get_env_data(name_df), silent = TRUE)
if (inherits(imported, "try-error") || NROW(imported) < 1) {
datamods:::toggle_widget(inputId = "confirm", enable = FALSE)
datamods:::insert_error(mssg = i18n$t(attr(imported, "condition")$message))
temporary_rv$status <- "error"
temporary_rv$data <- NULL
temporary_rv$name <- NULL
} else {
datamods:::toggle_widget(inputId = "confirm", enable = TRUE)
datamods:::insert_alert(
selector = ns("import"),
status = "success",
datamods:::make_success_alert(
imported,
trigger_return = trigger_return,
btn_show_data = btn_show_data
)
)
pkg <- attr(name_df, "package")
if (!is.null(pkg)) {
name <- paste(pkg, input$data, sep = "::")
} else {
name <- input$data
}
name <- trimws(sub("\\(([^\\)]+)\\)", "", name))
temporary_rv$status <- "success"
temporary_rv$data <- imported
temporary_rv$name <- name
}
}
}, ignoreInit = TRUE, ignoreNULL = FALSE)
observeEvent(input$see_data, {
show_data(temporary_rv$data, title = i18n$t("Imported data"), type = show_data_in)
})
observeEvent(input$confirm, {
imported_rv$data <- temporary_rv$data
imported_rv$name <- temporary_rv$name
})
if (identical(trigger_return, "button")) {
return(list(
status = reactive(temporary_rv$status),
name = reactive(imported_rv$name),
data = reactive(datamods:::as_out(imported_rv$data, return_class))
))
} else {
return(list(
status = reactive(temporary_rv$status),
name = reactive(temporary_rv$name),
data = reactive(datamods:::as_out(temporary_rv$data, return_class))
))
}
}
moduleServer(
id = id,
module = module
)
}
# utils -------------------------------------------------------------------
#' Get packages containing datasets
#'
#' @return a character vector of packages names
#' @export
#'
#' @importFrom utils data
#'
#' @examples
#' if (interactive()) {
#'
#' get_data_packages()
#'
#' }
get_data_packages <- function() {
suppressWarnings({
pkgs <- data(package = .packages(all.available = TRUE))
})
unique(pkgs$results[, 1])
}
#' List dataset contained in a package
#'
#' @param pkg Name of the package, must be installed.
#'
#' @return a \code{character} vector or \code{NULL}.
#' @export
#'
#' @importFrom utils data
#'
#' @examples
#'
#' list_pkg_data("ggplot2")
list_pkg_data <- function(pkg) {
if (isTRUE(requireNamespace(pkg, quietly = TRUE))) {
list_data <- data(package = pkg, envir = environment())$results[, "Item"]
list_data <- sort(list_data)
attr(list_data, "package") <- pkg
if (length(list_data) < 1) {
NULL
} else {
unname(list_data)
}
} else {
NULL
}
}
#' @importFrom utils data
get_env_data <- function(obj, env = globalenv()) {
pkg <- attr(obj, "package")
re <- regexpr(pattern = "\\(([^\\)]+)\\)", text = obj)
obj_ <- substr(x = obj, start = re + 1, stop = re + attr(re, "match.length") - 2)
obj <- gsub(pattern = "\\s.*", replacement = "", x = obj)
if (obj %in% ls(name = env)) {
get(x = obj, envir = env)
} else if (!is.null(pkg) && !identical(pkg, "")) {
res <- suppressWarnings(try(
get(utils::data(list = obj, package = pkg, envir = environment())), silent = TRUE
))
if (!inherits(res, "try-error"))
return(res)
data(list = obj_, package = pkg, envir = environment())
get(obj, envir = environment())
} else {
NULL
}
}
get_dimensions <- function(objs) {
if (is.null(objs))
return(NULL)
dataframes_dims <- Map(
f = function(name, pkg) {
attr(name, "package") <- pkg
tmp <- suppressWarnings(get_env_data(name))
if (is.data.frame(tmp)) {
sprintf("%d obs. of %d variables", nrow(tmp), ncol(tmp))
} else {
i18n$t("Not a data.frame")
}
},
name = objs,
pkg = if (!is.null(attr(objs, "package"))) {
attr(objs, "package")
} else {
character(1)
}
)
unlist(dataframes_dims)
}
########
#### Current file: /Users/au301842/FreesearchR/R//import-file-ext.R
########
@ -4685,16 +5131,19 @@ data_missings_server <- function(id,
shiny::req(variabler)
if (is.null(variabler()) || variabler() == "" || !variabler() %in% names(datar())) {
tbl <- rv$data()
if (anyNA(datar())){
title <- i18n$t("No variable chosen for analysis")
} else {
title <- i18n$t("No missing observations")
}
} else {
tbl <- rv$data()|>
gtsummary::bold_p()
title <- glue::glue(i18n$t("Missing vs non-missing observations in the variable **'{variabler()}'**"))
}
out <- rv$data() |>
out <- tbl |>
gtsummary::as_gt() |>
gt::tab_header(title = gt::md(title))
@ -4875,7 +5324,7 @@ plot_box_single <- function(data, pri, sec=NULL, seed = 2103) {
#' Area proportional venn diagrams
#'
#' @description
#' THis is slightly modified from https://gist.github.com/danlooo/d23d8bcf8856c7dd8e86266097404ded
#' This is slightly modified from https://gist.github.com/danlooo/d23d8bcf8856c7dd8e86266097404ded
#'
#' This functions uses eulerr::euler to plot area proportional venn diagramms
#' but plots it using ggplot2
@ -4885,18 +5334,27 @@ plot_box_single <- function(data, pri, sec=NULL, seed = 2103) {
#' @param show_quantities whether to show number of intersecting elements
#' @param show_labels whether to show set names
#' @param ... further arguments passed to eulerr::euler
#'
#' @include data_plots.R
ggeulerr <- function(
combinations,
show_quantities = TRUE,
show_labels = TRUE,
...) {
# browser()
## Extracting labels
labs <- sapply(names(combinations),\(.x){
# browser()
get_label(combinations,.x)
})
data <-
eulerr::euler(combinations = combinations, ...) |>
## Set labels as variable names for nicer plotting
setNames(as.data.frame(combinations),labs) |>
eulerr::euler(...) |>
plot(quantities = show_quantities) |>
purrr::pluck("data")
tibble::as_tibble(data$ellipses, rownames = "Variables") |>
ggplot2::ggplot() +
ggforce::geom_ellipse(
@ -4912,7 +5370,8 @@ ggeulerr <- function(
dplyr::mutate(
label = labels |> purrr::map2(quantities, ~ {
if (!is.na(.x) && !is.na(.y) && show_labels) {
paste0(.x, "\n", sprintf(.y, fmt = "%.2g"))
paste0(.x, "\n", sprintf(.y, fmt = "%.4g"))
# glue::glue("{.x}\n{round(.y,0)}")
} else if (!is.na(.x) && show_labels) {
.x
} else if (!is.na(.y)) {
@ -4951,6 +5410,21 @@ ggeulerr <- function(
#' ) |> plot_euler("A", c("B", "C"), "D", seed = 4)
#' mtcars |> plot_euler("vs", "am", seed = 1)
#' mtcars |> plot_euler("vs", "am", "cyl", seed = 1)
#' stRoke::trial |>
#' dplyr::mutate(
#' mfi_cut = cut(mfi_6, c(0, 12, max(mfi_6, na.rm = TRUE))),
#' mdi_cut = cut(mdi_6, c(0, 20, max(mdi_6, na.rm = TRUE)))
#' ) |>
#' purrr::map2(
#' c(sapply(stRoke::trial, \(.x)REDCapCAST::get_attr(.x, attr = "label")), "Fatigue", "Depression"),
#' \(.x, .y){
#' REDCapCAST::set_attr(.x, .y, "label")
#' }
#' ) |>
#' dplyr::bind_cols() |>
#' plot_euler("mfi_cut", "mdi_cut")
#' stRoke::trial |>
#' plot_euler(pri="male", sec=c("hypertension"))
plot_euler <- function(data, pri, sec, ter = NULL, seed = 2103) {
set.seed(seed = seed)
if (!is.null(ter)) {
@ -4958,16 +5432,13 @@ plot_euler <- function(data, pri, sec, ter = NULL, seed = 2103) {
} else {
ds <- list(data)
}
out <- lapply(ds, \(.x){
.x[c(pri, sec)] |>
as.data.frame() |>
na.omit() |>
plot_euler_single()
})
# browser()
wrap_plot_list(out,title=glue::glue("Grouped by {get_label(data,ter)}"))
# patchwork::wrap_plots(out)
wrap_plot_list(out, title = glue::glue(i18n$t("Grouped by {get_label(data,ter)}")))
}
#' Easily plot single euler diagrams
@ -6475,87 +6946,6 @@ regression_model_uv <- function(data,
### HELPERS
#' Data type assessment.
#'
#' @description
#' These are more overall than the native typeof. This is used to assess a more
#' meaningful "clinical" data type.
#'
#' @param data vector or data.frame. if data frame, each column is evaluated.
#'
#' @returns outcome type
#' @export
#'
#' @examples
#' mtcars |>
#' default_parsing() |>
#' lapply(data_type)
#' mtcars |>
#' default_parsing() |>
#' data_type()
#' c(1, 2) |> data_type()
#' 1 |> data_type()
#' c(rep(NA, 10)) |> data_type()
#' sample(1:100, 50) |> data_type()
#' factor(letters[1:20]) |> data_type()
#' as.Date(1:20) |> data_type()
data_type <- function(data) {
if (is.data.frame(data)) {
sapply(data, data_type)
} else {
cl_d <- class(data)
l_unique <- length(unique(na.omit(data)))
if (all(is.na(data))) {
out <- "empty"
} else if (l_unique < 2) {
out <- "monotone"
} else if (any(c("factor", "logical") %in% cl_d) | l_unique == 2) {
if (identical("logical", cl_d) | l_unique == 2) {
out <- "dichotomous"
} else {
# if (is.ordered(data)) {
# out <- "ordinal"
# } else {
out <- "categorical"
# }
}
} else if (identical(cl_d, "character")) {
out <- "text"
} else if (any(c("hms", "Date", "POSIXct", "POSIXt") %in% cl_d)) {
out <- "datetime"
} else if (l_unique > 2) {
## Previously had all thinkable classes
## Now just assumes the class has not been defined above
## any(c("numeric", "integer", "hms", "Date", "timediff") %in% cl_d) &
out <- "continuous"
} else {
out <- "unknown"
}
out
}
}
#' Recognised data types from data_type
#'
#' @returns vector
#' @export
#'
#' @examples
#' data_types()
data_types <- function() {
list(
"empty" = list(descr="Variable of all NAs",classes="Any class"),
"monotone" = list(descr="Variable with only one unique value",classes="Any class"),
"dichotomous" = list(descr="Variable with only two unique values",classes="Any class"),
"categorical"= list(descr="Factor variable",classes="factor (ordered or unordered)"),
"text"= list(descr="Character variable",classes="character"),
"datetime"= list(descr="Variable of time, date or datetime values",classes="hms, Date, POSIXct and POSIXt"),
"continuous"= list(descr="Numeric variable",classes="numeric, integer or double"),
"unknown"= list(descr="Anything not falling within the previous",classes="Any other class")
)
}
#' Implemented functions
#'
@ -7196,38 +7586,6 @@ symmetrical_scale_x_log10 <- function(plot, breaks = c(1, 2, 3, 5, 10), ...) {
#' purrr::map(regression_table) |>
#' tbl_merge()
#' }
#' regression_table <- function(x, ...) {
#' UseMethod("regression_table")
#' }
#'
#' #' @rdname regression_table
#' #' @export
#' regression_table.list <- function(x, ...) {
#' x |>
#' purrr::map(\(.m){
#' regression_table(x = .m, ...) |>
#' gtsummary::add_n()
#' }) |>
#' gtsummary::tbl_stack()
#' }
#'
#' #' @rdname regression_table
#' #' @export
#' regression_table.default <- function(x, ..., args.list = NULL, fun = "gtsummary::tbl_regression") {
#' # Stripping custom class
#' class(x) <- class(x)[class(x) != "freesearchr_model"]
#'
#' if (any(c(length(class(x)) != 1, class(x) != "lm"))) {
#' if (!"exponentiate" %in% names(args.list)) {
#' args.list <- c(args.list, list(exponentiate = TRUE))
#' }
#' }
#'
#' out <- do.call(getfun(fun), c(list(x = x), args.list))
#' out |>
#' gtsummary::add_glance_source_note() # |>
#' # gtsummary::bold_p()
#' }
regression_table <- function(x, ...) {
args <- list(...)
@ -7305,8 +7663,6 @@ tbl_merge <- function(data) {
}
}
# as_kable(tbl) |> write_lines(file=here::here("inst/apps/data_analysis_modules/www/_table1.md"))
# as_kable_extra(tbl)|> write_lines(file=here::here("inst/apps/data_analysis_modules/www/table1.md"))
########
@ -7387,13 +7743,15 @@ regression_ui <- function(id, ...) {
shiny::radioButtons(
inputId = ns("all"),
label = i18n$t("Specify covariables"),
inline = TRUE, selected = 2,
inline = TRUE,
selected = 2,
choiceNames = c(
"Yes",
"No"
),
choiceValues = c(1, 2)
),
# shiny::uiOutput(outputId = ns("all")),
shiny::conditionalPanel(
condition = "input.all==1",
shiny::uiOutput(outputId = ns("regression_vars")),
@ -7446,7 +7804,7 @@ regression_ui <- function(id, ...) {
)
),
bslib::nav_panel(
title = "Coefficient plot",
title = i18n$t("Coefficient plot"),
bslib::layout_sidebar(
sidebar = bslib::sidebar(
bslib::accordion(
@ -7558,11 +7916,6 @@ regression_server <- function(id,
}
})
shiny::observe({
bslib::accordion_panel_update(id = "acc_reg", target = "acc_pan_reg", title = i18n$t("Regression"))
bslib::accordion_panel_update(id = "acc_coef_plot", target = "acc_pan_coef_plot", title = i18n$t("Coefficients plot"))
bslib::accordion_panel_update(id = "acc_checks", target = "acc_pan_checks", title = i18n$t("Checks"))
})
output$data_info <- shiny::renderUI({
shiny::req(regression_vars())
@ -7570,6 +7923,31 @@ regression_server <- function(id,
data_description(data_r()[regression_vars()])
})
## Update on laguage change
shiny::observe({
bslib::accordion_panel_update(id = "acc_reg", target = "acc_pan_reg", title = i18n$t("Regression"))
bslib::accordion_panel_update(id = "acc_coef_plot", target = "acc_pan_coef_plot", title = i18n$t("Coefficients plot"))
bslib::accordion_panel_update(id = "acc_checks", target = "acc_pan_checks", title = i18n$t("Checks"))
})
# shiny::observe({
# shiny::updateRadioButtons(
# session = session,
# inputId = "all",
# label = i18n$t("Specify covariables"),
# # inline = TRUE,
# # selected = 2,
# choiceNames = c(
# i18n$t("Yes"),
# i18n$t("No")
# ),
# choiceValues = c(1, 2)
# )
# })
##############################################################################
#########
######### Input fields
@ -7593,7 +7971,7 @@ regression_server <- function(id,
columnSelectInput(
inputId = ns("outcome_var"),
selected = NULL,
label = "Select outcome variable",
label = i18n$t("Select outcome variable"),
data = data_r(),
multiple = FALSE
)
@ -7603,7 +7981,7 @@ regression_server <- function(id,
shiny::req(input$outcome_var)
shiny::selectizeInput(
inputId = ns("regression_type"),
label = "Choose regression analysis",
label = i18n$t("Choose regression analysis"),
## The below ifelse statement handles the case of loading a new dataset
choices = possible_functions(
data = dplyr::select(
@ -7622,7 +8000,7 @@ regression_server <- function(id,
shiny::selectizeInput(
inputId = ns("factor_vars"),
selected = colnames(data_r())[sapply(data_r(), is.factor)],
label = "Covariables to format as categorical",
label = i18n$t("Covariables to format as categorical"),
choices = colnames(data_r()),
multiple = TRUE
)
@ -7642,7 +8020,7 @@ regression_server <- function(id,
columnSelectInput(
inputId = ns("strat_var"),
selected = "none",
label = "Select variable to stratify baseline",
label = i18n$t("Select variable to stratify baseline"),
data = data_r(),
col_subset = c(
"none",
@ -7657,7 +8035,7 @@ regression_server <- function(id,
shiny::selectInput(
inputId = ns("plot_model"),
selected = 1,
label = "Select models to plot",
label = i18n$t("Select models to plot"),
choices = names(rv$list$regression$tables),
multiple = TRUE
)
@ -7707,7 +8085,7 @@ regression_server <- function(id,
rv$list$regression$models <- model_lists
},
error = function(err) {
showNotification(paste0("Creating regression models failed with the following error: ", err), type = "err")
showNotification(paste(i18n$t("Creating regression models failed with the following error:"), err), type = "err")
}
)
}
@ -7772,7 +8150,7 @@ regression_server <- function(id,
showNotification(paste0(warn), type = "warning")
},
error = function(err) {
showNotification(paste0("Creating a regression table failed with the following error: ", err), type = "err")
showNotification(paste(i18n$t("Creating a regression table failed with the following error:"), err), type = "err")
}
)
}
@ -7873,7 +8251,7 @@ regression_server <- function(id,
output$download_plot <- shiny::downloadHandler(
filename = paste0("regression_plot.", input$plot_type),
content = function(file) {
shiny::withProgress(message = "Saving the plot. Hold on for a moment..", {
shiny::withProgress(message = i18n$t("Saving the plot. Hold on for a moment.."), {
ggplot2::ggsave(
filename = file,
plot = rv$plot,
@ -7910,7 +8288,7 @@ regression_server <- function(id,
# showNotification(paste0(warn), type = "warning")
# },
error = function(err) {
showNotification(paste0("Running model assumptions checks failed with the following error: ", err), type = "err")
showNotification(paste(i18n$t("Running model assumptions checks failed with the following error:"), err), type = "err")
}
)
}
@ -7931,7 +8309,7 @@ regression_server <- function(id,
vectorSelectInput(
inputId = ns("plot_checks"),
selected = 1,
label = "Select checks to plot",
label = i18n$t("Select checks to plot"),
choices = names,
multiple = TRUE
)
@ -7946,7 +8324,7 @@ regression_server <- function(id,
if (!is.null(rv$list$regression$tables)) {
p <- rv$check_plot() +
# patchwork::wrap_plots() +
patchwork::plot_annotation(title = "Multivariable regression model checks")
patchwork::plot_annotation(title = i18n$t("Multivariable regression model checks"))
layout <- sapply(seq_len(length(p)), \(.x){
@ -8325,7 +8703,7 @@ ui_elements <- function(selection) {
# ),
shiny::selectInput(
inputId = "source",
label="",
label = "",
selected = "file",
choices = "file",
width = "100%"
@ -8361,7 +8739,11 @@ ui_elements <- function(selection) {
),
shiny::conditionalPanel(
condition = "input.source=='env'",
import_globalenv_ui(id = "env", title = NULL)
import_globalenv_ui(
id = "env",
title = NULL,
packages = c("NHANES", "stRoke")
)
),
# shiny::conditionalPanel(
# condition = "input.source=='redcap'",
@ -8615,7 +8997,7 @@ ui_elements <- function(selection) {
sidebar = bslib::sidebar(
shiny::uiOutput(outputId = "data_info_nochar", inline = TRUE),
bslib::accordion(
id="acc_chars",
id = "acc_chars",
open = "acc_chars",
multiple = FALSE,
bslib::accordion_panel(
@ -8661,7 +9043,7 @@ ui_elements <- function(selection) {
sidebar = bslib::sidebar(
# shiny::uiOutput(outputId = "data_info_nochar", inline = TRUE),
bslib::accordion(
id="acc_cor",
id = "acc_cor",
open = "acc_chars",
multiple = FALSE,
bslib::accordion_panel(
@ -10979,6 +11361,7 @@ ui <- bslib::page_fixed(
## Code formatting dependencies
prismDependencies,
prismRDependency,
html_dependency_FreesearchR(),
## Version dependent header
header_include(),
## This adds the actual favicon
@ -11264,7 +11647,8 @@ server <- function(input, output, session) {
rv$code <- modifyList(x = rv$code, list(import = from_redcap$code()))
})
from_env <- datamods::import_globalenv_server(
# from_env <- datamods::import_globalenv_server(
from_env <- import_globalenv_server(
id = "env",
trigger_return = "change",
btn_show_data = FALSE,

View file

@ -219,3 +219,28 @@
"Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.","Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access."
"Click to see the imported data","Click to see the imported data"
"Regression table","Regression table"
"Import a dataset from an environment","Import a dataset from an environment"
"Select a dataset:","Vælg datasæt:"
"List of datasets...","List of datasets..."
"No data selected!","Ingen data valgt!"
"Use a datasat from your environment or from the environment of a package.","Use a datasat from your environment or from the environment of a package."
"No dataset here...","Ingen datasæt her..."
"Use a dataset from your environment or from the environment of a package.","Use a dataset from your environment or from the environment of a package."
"Not a data.frame","Ikke en data.frame"
"Select source","Vælg datakilde"
"Select a data source:","Vælg datakilde:"
"Yes","Ja"
"No","Nej"
"Coefficient plot","Coefficient plot"
"Select outcome variable","Select outcome variable"
"Choose regression analysis","Choose regression analysis"
"Covariables to format as categorical","Covariables to format as categorical"
"Select variable to stratify baseline","Select variable to stratify baseline"
"Select models to plot","Select models to plot"
"Creating regression models failed with the following error:","Creating regression models failed with the following error:"
"Creating a regression table failed with the following error:","Creating a regression table failed with the following error:"
"Saving the plot. Hold on for a moment..","Saving the plot. Hold on for a moment.."
"Running model assumptions checks failed with the following error:","Running model assumptions checks failed with the following error:"
"Select checks to plot","Select checks to plot"
"Multivariable regression model checks","Multivariable regression model checks"
"Grouped by {get_label(data,ter)}","Grouped by {get_label(data,ter)}"

1 en da
219 Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access. Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.
220 Click to see the imported data Click to see the imported data
221 Regression table Regression table
222 Import a dataset from an environment Import a dataset from an environment
223 Select a dataset: Vælg datasæt:
224 List of datasets... List of datasets...
225 No data selected! Ingen data valgt!
226 Use a datasat from your environment or from the environment of a package. Use a datasat from your environment or from the environment of a package.
227 No dataset here... Ingen datasæt her...
228 Use a dataset from your environment or from the environment of a package. Use a dataset from your environment or from the environment of a package.
229 Not a data.frame Ikke en data.frame
230 Select source Vælg datakilde
231 Select a data source: Vælg datakilde:
232 Yes Ja
233 No Nej
234 Coefficient plot Coefficient plot
235 Select outcome variable Select outcome variable
236 Choose regression analysis Choose regression analysis
237 Covariables to format as categorical Covariables to format as categorical
238 Select variable to stratify baseline Select variable to stratify baseline
239 Select models to plot Select models to plot
240 Creating regression models failed with the following error: Creating regression models failed with the following error:
241 Creating a regression table failed with the following error: Creating a regression table failed with the following error:
242 Saving the plot. Hold on for a moment.. Saving the plot. Hold on for a moment..
243 Running model assumptions checks failed with the following error: Running model assumptions checks failed with the following error:
244 Select checks to plot Select checks to plot
245 Multivariable regression model checks Multivariable regression model checks
246 Grouped by {get_label(data,ter)} Grouped by {get_label(data,ter)}

View file

@ -219,3 +219,28 @@
"Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.","Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access."
"Click to see the imported data","Click to see the imported data"
"Regression table","Regression table"
"Import a dataset from an environment","Import a dataset from an environment"
"Select a dataset:","Select a dataset:"
"List of datasets...","List of datasets..."
"No data selected!","No data selected!"
"Use a datasat from your environment or from the environment of a package.","Use a datasat from your environment or from the environment of a package."
"No dataset here...","No dataset here..."
"Use a dataset from your environment or from the environment of a package.","Use a dataset from your environment or from the environment of a package."
"Not a data.frame","Not a data.frame"
"Select source","Select source"
"Select a data source:","Select a data source:"
"Yes","Yes"
"No","No"
"Coefficient plot","Coefficient plot"
"Select outcome variable","Select outcome variable"
"Choose regression analysis","Choose regression analysis"
"Covariables to format as categorical","Covariables to format as categorical"
"Select variable to stratify baseline","Select variable to stratify baseline"
"Select models to plot","Select models to plot"
"Creating regression models failed with the following error:","Creating regression models failed with the following error:"
"Creating a regression table failed with the following error:","Creating a regression table failed with the following error:"
"Saving the plot. Hold on for a moment..","Saving the plot. Hold on for a moment.."
"Running model assumptions checks failed with the following error:","Running model assumptions checks failed with the following error:"
"Select checks to plot","Select checks to plot"
"Multivariable regression model checks","Multivariable regression model checks"
"Grouped by {get_label(data,ter)}","Grouped by {get_label(data,ter)}"

1 en sw
219 Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access. Data retrieved, but it looks like not all requested fields were retrieved from the server. Please check with your REDCap administrator that you have required permissions for data access.
220 Click to see the imported data Click to see the imported data
221 Regression table Regression table
222 Import a dataset from an environment Import a dataset from an environment
223 Select a dataset: Select a dataset:
224 List of datasets... List of datasets...
225 No data selected! No data selected!
226 Use a datasat from your environment or from the environment of a package. Use a datasat from your environment or from the environment of a package.
227 No dataset here... No dataset here...
228 Use a dataset from your environment or from the environment of a package. Use a dataset from your environment or from the environment of a package.
229 Not a data.frame Not a data.frame
230 Select source Select source
231 Select a data source: Select a data source:
232 Yes Yes
233 No No
234 Coefficient plot Coefficient plot
235 Select outcome variable Select outcome variable
236 Choose regression analysis Choose regression analysis
237 Covariables to format as categorical Covariables to format as categorical
238 Select variable to stratify baseline Select variable to stratify baseline
239 Select models to plot Select models to plot
240 Creating regression models failed with the following error: Creating regression models failed with the following error:
241 Creating a regression table failed with the following error: Creating a regression table failed with the following error:
242 Saving the plot. Hold on for a moment.. Saving the plot. Hold on for a moment..
243 Running model assumptions checks failed with the following error: Running model assumptions checks failed with the following error:
244 Select checks to plot Select checks to plot
245 Multivariable regression model checks Multivariable regression model checks
246 Grouped by {get_label(data,ter)} Grouped by {get_label(data,ter)}

View file

@ -1,7 +1,7 @@
########
#### Current file: /var/folders/9l/xbc19wxx0g79jdd2sf_0v291mhwh7f/T//Rtmpo2rU34/file15cb31846160a.R
#### Current file: /var/folders/9l/xbc19wxx0g79jdd2sf_0v291mhwh7f/T//RtmpWiu9wh/file1e99785ae783.R
########
i18n_path <- system.file("translations", package = "FreesearchR")
@ -62,7 +62,7 @@ i18n$set_translation_language("en")
#### Current file: /Users/au301842/FreesearchR/R//app_version.R
########
app_version <- function()'25.9.2'
app_version <- function()'25.10.1'
########
@ -3433,7 +3433,8 @@ dummy_Imports <- function() {
parameters::ci(),
DT::addRow(),
bslib::accordion(),
NHANES::NHANES()
NHANES::NHANES(),
stRoke::add_padding()
)
# https://github.com/hadley/r-pkgs/issues/828
}
@ -3948,12 +3949,93 @@ simple_snake <- function(data){
gsub("[\\s+]","_",gsub("[^\\w\\s:-]", "", tolower(data), perl=TRUE), perl=TRUE)
}
#' Data type assessment.
#'
#' @description
#' These are more overall than the native typeof. This is used to assess a more
#' meaningful "clinical" data type.
#'
#' @param data vector or data.frame. if data frame, each column is evaluated.
#'
#' @returns outcome type
#' @export
#'
#' @examples
#' mtcars |>
#' default_parsing() |>
#' lapply(data_type)
#' mtcars |>
#' default_parsing() |>
#' data_type()
#' c(1, 2) |> data_type()
#' 1 |> data_type()
#' c(rep(NA, 10)) |> data_type()
#' sample(1:100, 50) |> data_type()
#' factor(letters[1:20]) |> data_type()
#' as.Date(1:20) |> data_type()
data_type <- function(data) {
if (is.data.frame(data)) {
sapply(data, data_type)
} else {
cl_d <- class(data)
l_unique <- length(unique(na.omit(data)))
if (all(is.na(data))) {
out <- "empty"
} else if (l_unique < 2) {
out <- "monotone"
} else if (any(c("factor", "logical") %in% cl_d) | l_unique == 2) {
if (identical("logical", cl_d) | l_unique == 2) {
out <- "dichotomous"
} else {
# if (is.ordered(data)) {
# out <- "ordinal"
# } else {
out <- "categorical"
# }
}
} else if (identical(cl_d, "character")) {
out <- "text"
} else if (any(c("hms", "Date", "POSIXct", "POSIXt") %in% cl_d)) {
out <- "datetime"
} else if (l_unique > 2) {
## Previously had all thinkable classes
## Now just assumes the class has not been defined above
## any(c("numeric", "integer", "hms", "Date", "timediff") %in% cl_d) &
out <- "continuous"
} else {
out <- "unknown"
}
out
}
}
#' Recognised data types from data_type
#'
#' @returns vector
#' @export
#'
#' @examples
#' data_types()
data_types <- function() {
list(
"empty" = list(descr="Variable of all NAs",classes="Any class"),
"monotone" = list(descr="Variable with only one unique value",classes="Any class"),
"dichotomous" = list(descr="Variable with only two unique values",classes="Any class"),
"categorical"= list(descr="Factor variable",classes="factor (ordered or unordered)"),
"text"= list(descr="Character variable",classes="character"),
"datetime"= list(descr="Variable of time, date or datetime values",classes="hms, Date, POSIXct and POSIXt"),
"continuous"= list(descr="Numeric variable",classes="numeric, integer or double"),
"unknown"= list(descr="Anything not falling within the previous",classes="Any other class")
)
}
########
#### Current file: /Users/au301842/FreesearchR/R//hosted_version.R
########
hosted_version <- function()'v25.9.2-250925'
hosted_version <- function()'v25.10.1-251002'
########
@ -3966,11 +4048,375 @@ html_dependency_FreesearchR <- function() {
version = packageVersion("FreesearchR"),
src = list(href = "FreesearchR", file = "assets"),
package = "FreesearchR",
script = "js/FreesearchR.js",
stylesheet = "css/FreesearchR.css"
)
}
########
#### Current file: /Users/au301842/FreesearchR/R//import_globalenv-ext.R
########
#' @title Import data from an Environment
#'
#' @description Let the user select a dataset from its own environment or from a package's environment.
#' Modified from datamods
#'
#' @param id Module's ID.
#' @param globalenv Search for data in Global environment.
#' @param packages Name of packages in which to search data.
#' @param title Module's title, if `TRUE` use the default title,
#' use `NULL` for no title or a `shiny.tag` for a custom one.
#'
#' @export
#'
#' @name import-globalenv
#'
import_globalenv_ui <- function(id,
globalenv = TRUE,
packages = datamods::get_data_packages(),
title = TRUE) {
ns <- NS(id)
choices <- list()
if (isTRUE(globalenv)) {
choices <- append(choices, "Global Environment")
}
if (!is.null(packages)) {
choices <- append(choices, list(Packages = as.character(packages)))
}
if (isTRUE(globalenv)) {
selected <- "Global Environment"
} else {
selected <- packages[1]
}
if (isTRUE(title)) {
title <- tags$h4(
i18n$t("Import a dataset from an environment"),
class = "datamods-title"
)
}
tags$div(
class = "datamods-import",
datamods:::html_dependency_datamods(),
title,
shinyWidgets::pickerInput(
inputId = ns("env"),
label = i18n$t("Select a data source:"),
choices = choices,
selected = selected,
width = "100%",
options = list(
"title" = i18n$t("Select source"),
"live-search" = TRUE,
"size" = 10
)
),
shinyWidgets::pickerInput(
inputId = ns("data"),
label = i18n$t("Select a dataset:"),
# selected = character(0),
choices = NULL,
# options = list(title = i18n$t("List of datasets...")),
width = "100%"
),
tags$div(
id = ns("import-placeholder"),
shinyWidgets::alert(
id = ns("import-result"),
status = "info",
tags$b(i18n$t("No data selected!")),
i18n$t("Use a datasat from your environment or from the environment of a package."),
dismissible = TRUE
)
),
uiOutput(
outputId = ns("container_valid_btn"),
style = "margin-top: 20px;"
)
)
}
#' @param btn_show_data Display or not a button to display data in a modal window if import is successful.
#' @param show_data_in Where to display data: in a `"popup"` or in a `"modal"` window.
#' @param trigger_return When to update selected data:
#' `"button"` (when user click on button) or
#' `"change"` (each time user select a dataset in the list).
#' @param return_class Class of returned data: `data.frame`, `data.table`, `tbl_df` (tibble) or `raw`.
#' @param reset A `reactive` function that when triggered resets the data.
#'
#' @export
#'
#' @importFrom shiny moduleServer reactiveValues observeEvent reactive removeUI is.reactive icon actionLink isTruthy
#' @importFrom htmltools tags tagList
#' @importFrom shinyWidgets updatePickerInput
#'
#' @rdname import-globalenv
import_globalenv_server <- function(id,
btn_show_data = TRUE,
show_data_in = c("popup", "modal"),
trigger_return = c("button", "change"),
return_class = c("data.frame", "data.table", "tbl_df", "raw"),
reset = reactive(NULL)) {
trigger_return <- match.arg(trigger_return)
return_class <- match.arg(return_class)
module <- function(input, output, session) {
ns <- session$ns
imported_rv <- reactiveValues(data = NULL, name = NULL)
temporary_rv <- reactiveValues(data = NULL, name = NULL, status = NULL)
observeEvent(reset(), {
temporary_rv$data <- NULL
temporary_rv$name <- NULL
temporary_rv$status <- NULL
})
output$container_valid_btn <- renderUI({
if (identical(trigger_return, "button")) {
button_import()
}
})
observeEvent(input$env, {
if (identical(input$env, "Global Environment")) {
choices <- datamods:::search_obj("data.frame")
} else {
choices <- datamods:::list_pkg_data(input$env)
}
if (is.null(choices)) {
choices <- i18n$t("No dataset here...")
choicesOpt <- list(disabled = TRUE)
} else {
choicesOpt <- list(
subtext = datamods:::get_dimensions(choices)
)
}
temporary_rv$package <- attr(choices, "package")
shinyWidgets::updatePickerInput(
session = session,
inputId = "data",
selected = character(0),
choices = choices,
choicesOpt = choicesOpt,
options = list(title = i18n$t("List of datasets..."))
)
})
observe(
shinyWidgets::alert(
id = "import-result",
status = "info",
tags$b(i18n$t("No data selected!")),
i18n$t("Use a datasat from your environment or from the environment of a package."),
dismissible = TRUE
)
)
observeEvent(input$trigger, {
if (identical(trigger_return, "change")) {
datamods:::hideUI(selector = paste0("#", ns("container_valid_btn")))
}
})
observeEvent(input$data, {
if (!isTruthy(input$data)) {
datamods:::toggle_widget(inputId = "confirm", enable = FALSE)
datamods:::insert_alert(
selector = ns("import"),
status = "info",
tags$b(i18n$t("No data selected!")),
i18n$t("Use a dataset from your environment or from the environment of a package.")
)
} else {
name_df <- input$data
if (!is.null(temporary_rv$package)) {
attr(name_df, "package") <- temporary_rv$package
}
imported <- try(get_env_data(name_df), silent = TRUE)
if (inherits(imported, "try-error") || NROW(imported) < 1) {
datamods:::toggle_widget(inputId = "confirm", enable = FALSE)
datamods:::insert_error(mssg = i18n$t(attr(imported, "condition")$message))
temporary_rv$status <- "error"
temporary_rv$data <- NULL
temporary_rv$name <- NULL
} else {
datamods:::toggle_widget(inputId = "confirm", enable = TRUE)
datamods:::insert_alert(
selector = ns("import"),
status = "success",
datamods:::make_success_alert(
imported,
trigger_return = trigger_return,
btn_show_data = btn_show_data
)
)
pkg <- attr(name_df, "package")
if (!is.null(pkg)) {
name <- paste(pkg, input$data, sep = "::")
} else {
name <- input$data
}
name <- trimws(sub("\\(([^\\)]+)\\)", "", name))
temporary_rv$status <- "success"
temporary_rv$data <- imported
temporary_rv$name <- name
}
}
}, ignoreInit = TRUE, ignoreNULL = FALSE)
observeEvent(input$see_data, {
show_data(temporary_rv$data, title = i18n$t("Imported data"), type = show_data_in)
})
observeEvent(input$confirm, {
imported_rv$data <- temporary_rv$data
imported_rv$name <- temporary_rv$name
})
if (identical(trigger_return, "button")) {
return(list(
status = reactive(temporary_rv$status),
name = reactive(imported_rv$name),
data = reactive(datamods:::as_out(imported_rv$data, return_class))
))
} else {
return(list(
status = reactive(temporary_rv$status),
name = reactive(temporary_rv$name),
data = reactive(datamods:::as_out(temporary_rv$data, return_class))
))
}
}
moduleServer(
id = id,
module = module
)
}
# utils -------------------------------------------------------------------
#' Get packages containing datasets
#'
#' @return a character vector of packages names
#' @export
#'
#' @importFrom utils data
#'
#' @examples
#' if (interactive()) {
#'
#' get_data_packages()
#'
#' }
get_data_packages <- function() {
suppressWarnings({
pkgs <- data(package = .packages(all.available = TRUE))
})
unique(pkgs$results[, 1])
}
#' List dataset contained in a package
#'
#' @param pkg Name of the package, must be installed.
#'
#' @return a \code{character} vector or \code{NULL}.
#' @export
#'
#' @importFrom utils data
#'
#' @examples
#'
#' list_pkg_data("ggplot2")
list_pkg_data <- function(pkg) {
if (isTRUE(requireNamespace(pkg, quietly = TRUE))) {
list_data <- data(package = pkg, envir = environment())$results[, "Item"]
list_data <- sort(list_data)
attr(list_data, "package") <- pkg
if (length(list_data) < 1) {
NULL
} else {
unname(list_data)
}
} else {
NULL
}
}
#' @importFrom utils data
get_env_data <- function(obj, env = globalenv()) {
pkg <- attr(obj, "package")
re <- regexpr(pattern = "\\(([^\\)]+)\\)", text = obj)
obj_ <- substr(x = obj, start = re + 1, stop = re + attr(re, "match.length") - 2)
obj <- gsub(pattern = "\\s.*", replacement = "", x = obj)
if (obj %in% ls(name = env)) {
get(x = obj, envir = env)
} else if (!is.null(pkg) && !identical(pkg, "")) {
res <- suppressWarnings(try(
get(utils::data(list = obj, package = pkg, envir = environment())), silent = TRUE
))
if (!inherits(res, "try-error"))
return(res)
data(list = obj_, package = pkg, envir = environment())
get(obj, envir = environment())
} else {
NULL
}
}
get_dimensions <- function(objs) {
if (is.null(objs))
return(NULL)
dataframes_dims <- Map(
f = function(name, pkg) {
attr(name, "package") <- pkg
tmp <- suppressWarnings(get_env_data(name))
if (is.data.frame(tmp)) {
sprintf("%d obs. of %d variables", nrow(tmp), ncol(tmp))
} else {
i18n$t("Not a data.frame")
}
},
name = objs,
pkg = if (!is.null(attr(objs, "package"))) {
attr(objs, "package")
} else {
character(1)
}
)
unlist(dataframes_dims)
}
########
#### Current file: /Users/au301842/FreesearchR/R//import-file-ext.R
########
@ -4685,16 +5131,19 @@ data_missings_server <- function(id,
shiny::req(variabler)
if (is.null(variabler()) || variabler() == "" || !variabler() %in% names(datar())) {
tbl <- rv$data()
if (anyNA(datar())){
title <- i18n$t("No variable chosen for analysis")
} else {
title <- i18n$t("No missing observations")
}
} else {
tbl <- rv$data()|>
gtsummary::bold_p()
title <- glue::glue(i18n$t("Missing vs non-missing observations in the variable **'{variabler()}'**"))
}
out <- rv$data() |>
out <- tbl |>
gtsummary::as_gt() |>
gt::tab_header(title = gt::md(title))
@ -4875,7 +5324,7 @@ plot_box_single <- function(data, pri, sec=NULL, seed = 2103) {
#' Area proportional venn diagrams
#'
#' @description
#' THis is slightly modified from https://gist.github.com/danlooo/d23d8bcf8856c7dd8e86266097404ded
#' This is slightly modified from https://gist.github.com/danlooo/d23d8bcf8856c7dd8e86266097404ded
#'
#' This functions uses eulerr::euler to plot area proportional venn diagramms
#' but plots it using ggplot2
@ -4885,18 +5334,27 @@ plot_box_single <- function(data, pri, sec=NULL, seed = 2103) {
#' @param show_quantities whether to show number of intersecting elements
#' @param show_labels whether to show set names
#' @param ... further arguments passed to eulerr::euler
#'
#' @include data_plots.R
ggeulerr <- function(
combinations,
show_quantities = TRUE,
show_labels = TRUE,
...) {
# browser()
## Extracting labels
labs <- sapply(names(combinations),\(.x){
# browser()
get_label(combinations,.x)
})
data <-
eulerr::euler(combinations = combinations, ...) |>
## Set labels as variable names for nicer plotting
setNames(as.data.frame(combinations),labs) |>
eulerr::euler(...) |>
plot(quantities = show_quantities) |>
purrr::pluck("data")
tibble::as_tibble(data$ellipses, rownames = "Variables") |>
ggplot2::ggplot() +
ggforce::geom_ellipse(
@ -4912,7 +5370,8 @@ ggeulerr <- function(
dplyr::mutate(
label = labels |> purrr::map2(quantities, ~ {
if (!is.na(.x) && !is.na(.y) && show_labels) {
paste0(.x, "\n", sprintf(.y, fmt = "%.2g"))
paste0(.x, "\n", sprintf(.y, fmt = "%.4g"))
# glue::glue("{.x}\n{round(.y,0)}")
} else if (!is.na(.x) && show_labels) {
.x
} else if (!is.na(.y)) {
@ -4951,6 +5410,21 @@ ggeulerr <- function(
#' ) |> plot_euler("A", c("B", "C"), "D", seed = 4)
#' mtcars |> plot_euler("vs", "am", seed = 1)
#' mtcars |> plot_euler("vs", "am", "cyl", seed = 1)
#' stRoke::trial |>
#' dplyr::mutate(
#' mfi_cut = cut(mfi_6, c(0, 12, max(mfi_6, na.rm = TRUE))),
#' mdi_cut = cut(mdi_6, c(0, 20, max(mdi_6, na.rm = TRUE)))
#' ) |>
#' purrr::map2(
#' c(sapply(stRoke::trial, \(.x)REDCapCAST::get_attr(.x, attr = "label")), "Fatigue", "Depression"),
#' \(.x, .y){
#' REDCapCAST::set_attr(.x, .y, "label")
#' }
#' ) |>
#' dplyr::bind_cols() |>
#' plot_euler("mfi_cut", "mdi_cut")
#' stRoke::trial |>
#' plot_euler(pri="male", sec=c("hypertension"))
plot_euler <- function(data, pri, sec, ter = NULL, seed = 2103) {
set.seed(seed = seed)
if (!is.null(ter)) {
@ -4958,16 +5432,13 @@ plot_euler <- function(data, pri, sec, ter = NULL, seed = 2103) {
} else {
ds <- list(data)
}
out <- lapply(ds, \(.x){
.x[c(pri, sec)] |>
as.data.frame() |>
na.omit() |>
plot_euler_single()
})
# browser()
wrap_plot_list(out,title=glue::glue("Grouped by {get_label(data,ter)}"))
# patchwork::wrap_plots(out)
wrap_plot_list(out, title = glue::glue(i18n$t("Grouped by {get_label(data,ter)}")))
}
#' Easily plot single euler diagrams
@ -6475,87 +6946,6 @@ regression_model_uv <- function(data,
### HELPERS
#' Data type assessment.
#'
#' @description
#' These are more overall than the native typeof. This is used to assess a more
#' meaningful "clinical" data type.
#'
#' @param data vector or data.frame. if data frame, each column is evaluated.
#'
#' @returns outcome type
#' @export
#'
#' @examples
#' mtcars |>
#' default_parsing() |>
#' lapply(data_type)
#' mtcars |>
#' default_parsing() |>
#' data_type()
#' c(1, 2) |> data_type()
#' 1 |> data_type()
#' c(rep(NA, 10)) |> data_type()
#' sample(1:100, 50) |> data_type()
#' factor(letters[1:20]) |> data_type()
#' as.Date(1:20) |> data_type()
data_type <- function(data) {
if (is.data.frame(data)) {
sapply(data, data_type)
} else {
cl_d <- class(data)
l_unique <- length(unique(na.omit(data)))
if (all(is.na(data))) {
out <- "empty"
} else if (l_unique < 2) {
out <- "monotone"
} else if (any(c("factor", "logical") %in% cl_d) | l_unique == 2) {
if (identical("logical", cl_d) | l_unique == 2) {
out <- "dichotomous"
} else {
# if (is.ordered(data)) {
# out <- "ordinal"
# } else {
out <- "categorical"
# }
}
} else if (identical(cl_d, "character")) {
out <- "text"
} else if (any(c("hms", "Date", "POSIXct", "POSIXt") %in% cl_d)) {
out <- "datetime"
} else if (l_unique > 2) {
## Previously had all thinkable classes
## Now just assumes the class has not been defined above
## any(c("numeric", "integer", "hms", "Date", "timediff") %in% cl_d) &
out <- "continuous"
} else {
out <- "unknown"
}
out
}
}
#' Recognised data types from data_type
#'
#' @returns vector
#' @export
#'
#' @examples
#' data_types()
data_types <- function() {
list(
"empty" = list(descr="Variable of all NAs",classes="Any class"),
"monotone" = list(descr="Variable with only one unique value",classes="Any class"),
"dichotomous" = list(descr="Variable with only two unique values",classes="Any class"),
"categorical"= list(descr="Factor variable",classes="factor (ordered or unordered)"),
"text"= list(descr="Character variable",classes="character"),
"datetime"= list(descr="Variable of time, date or datetime values",classes="hms, Date, POSIXct and POSIXt"),
"continuous"= list(descr="Numeric variable",classes="numeric, integer or double"),
"unknown"= list(descr="Anything not falling within the previous",classes="Any other class")
)
}
#' Implemented functions
#'
@ -7196,38 +7586,6 @@ symmetrical_scale_x_log10 <- function(plot, breaks = c(1, 2, 3, 5, 10), ...) {
#' purrr::map(regression_table) |>
#' tbl_merge()
#' }
#' regression_table <- function(x, ...) {
#' UseMethod("regression_table")
#' }
#'
#' #' @rdname regression_table
#' #' @export
#' regression_table.list <- function(x, ...) {
#' x |>
#' purrr::map(\(.m){
#' regression_table(x = .m, ...) |>
#' gtsummary::add_n()
#' }) |>
#' gtsummary::tbl_stack()
#' }
#'
#' #' @rdname regression_table
#' #' @export
#' regression_table.default <- function(x, ..., args.list = NULL, fun = "gtsummary::tbl_regression") {
#' # Stripping custom class
#' class(x) <- class(x)[class(x) != "freesearchr_model"]
#'
#' if (any(c(length(class(x)) != 1, class(x) != "lm"))) {
#' if (!"exponentiate" %in% names(args.list)) {
#' args.list <- c(args.list, list(exponentiate = TRUE))
#' }
#' }
#'
#' out <- do.call(getfun(fun), c(list(x = x), args.list))
#' out |>
#' gtsummary::add_glance_source_note() # |>
#' # gtsummary::bold_p()
#' }
regression_table <- function(x, ...) {
args <- list(...)
@ -7305,8 +7663,6 @@ tbl_merge <- function(data) {
}
}
# as_kable(tbl) |> write_lines(file=here::here("inst/apps/data_analysis_modules/www/_table1.md"))
# as_kable_extra(tbl)|> write_lines(file=here::here("inst/apps/data_analysis_modules/www/table1.md"))
########
@ -7387,13 +7743,15 @@ regression_ui <- function(id, ...) {
shiny::radioButtons(
inputId = ns("all"),
label = i18n$t("Specify covariables"),
inline = TRUE, selected = 2,
inline = TRUE,
selected = 2,
choiceNames = c(
"Yes",
"No"
),
choiceValues = c(1, 2)
),
# shiny::uiOutput(outputId = ns("all")),
shiny::conditionalPanel(
condition = "input.all==1",
shiny::uiOutput(outputId = ns("regression_vars")),
@ -7446,7 +7804,7 @@ regression_ui <- function(id, ...) {
)
),
bslib::nav_panel(
title = "Coefficient plot",
title = i18n$t("Coefficient plot"),
bslib::layout_sidebar(
sidebar = bslib::sidebar(
bslib::accordion(
@ -7558,11 +7916,6 @@ regression_server <- function(id,
}
})
shiny::observe({
bslib::accordion_panel_update(id = "acc_reg", target = "acc_pan_reg", title = i18n$t("Regression"))
bslib::accordion_panel_update(id = "acc_coef_plot", target = "acc_pan_coef_plot", title = i18n$t("Coefficients plot"))
bslib::accordion_panel_update(id = "acc_checks", target = "acc_pan_checks", title = i18n$t("Checks"))
})
output$data_info <- shiny::renderUI({
shiny::req(regression_vars())
@ -7570,6 +7923,31 @@ regression_server <- function(id,
data_description(data_r()[regression_vars()])
})
## Update on laguage change
shiny::observe({
bslib::accordion_panel_update(id = "acc_reg", target = "acc_pan_reg", title = i18n$t("Regression"))
bslib::accordion_panel_update(id = "acc_coef_plot", target = "acc_pan_coef_plot", title = i18n$t("Coefficients plot"))
bslib::accordion_panel_update(id = "acc_checks", target = "acc_pan_checks", title = i18n$t("Checks"))
})
# shiny::observe({
# shiny::updateRadioButtons(
# session = session,
# inputId = "all",
# label = i18n$t("Specify covariables"),
# # inline = TRUE,
# # selected = 2,
# choiceNames = c(
# i18n$t("Yes"),
# i18n$t("No")
# ),
# choiceValues = c(1, 2)
# )
# })
##############################################################################
#########
######### Input fields
@ -7593,7 +7971,7 @@ regression_server <- function(id,
columnSelectInput(
inputId = ns("outcome_var"),
selected = NULL,
label = "Select outcome variable",
label = i18n$t("Select outcome variable"),
data = data_r(),
multiple = FALSE
)
@ -7603,7 +7981,7 @@ regression_server <- function(id,
shiny::req(input$outcome_var)
shiny::selectizeInput(
inputId = ns("regression_type"),
label = "Choose regression analysis",
label = i18n$t("Choose regression analysis"),
## The below ifelse statement handles the case of loading a new dataset
choices = possible_functions(
data = dplyr::select(
@ -7622,7 +8000,7 @@ regression_server <- function(id,
shiny::selectizeInput(
inputId = ns("factor_vars"),
selected = colnames(data_r())[sapply(data_r(), is.factor)],
label = "Covariables to format as categorical",
label = i18n$t("Covariables to format as categorical"),
choices = colnames(data_r()),
multiple = TRUE
)
@ -7642,7 +8020,7 @@ regression_server <- function(id,
columnSelectInput(
inputId = ns("strat_var"),
selected = "none",
label = "Select variable to stratify baseline",
label = i18n$t("Select variable to stratify baseline"),
data = data_r(),
col_subset = c(
"none",
@ -7657,7 +8035,7 @@ regression_server <- function(id,
shiny::selectInput(
inputId = ns("plot_model"),
selected = 1,
label = "Select models to plot",
label = i18n$t("Select models to plot"),
choices = names(rv$list$regression$tables),
multiple = TRUE
)
@ -7707,7 +8085,7 @@ regression_server <- function(id,
rv$list$regression$models <- model_lists
},
error = function(err) {
showNotification(paste0("Creating regression models failed with the following error: ", err), type = "err")
showNotification(paste(i18n$t("Creating regression models failed with the following error:"), err), type = "err")
}
)
}
@ -7772,7 +8150,7 @@ regression_server <- function(id,
showNotification(paste0(warn), type = "warning")
},
error = function(err) {
showNotification(paste0("Creating a regression table failed with the following error: ", err), type = "err")
showNotification(paste(i18n$t("Creating a regression table failed with the following error:"), err), type = "err")
}
)
}
@ -7873,7 +8251,7 @@ regression_server <- function(id,
output$download_plot <- shiny::downloadHandler(
filename = paste0("regression_plot.", input$plot_type),
content = function(file) {
shiny::withProgress(message = "Saving the plot. Hold on for a moment..", {
shiny::withProgress(message = i18n$t("Saving the plot. Hold on for a moment.."), {
ggplot2::ggsave(
filename = file,
plot = rv$plot,
@ -7910,7 +8288,7 @@ regression_server <- function(id,
# showNotification(paste0(warn), type = "warning")
# },
error = function(err) {
showNotification(paste0("Running model assumptions checks failed with the following error: ", err), type = "err")
showNotification(paste(i18n$t("Running model assumptions checks failed with the following error:"), err), type = "err")
}
)
}
@ -7931,7 +8309,7 @@ regression_server <- function(id,
vectorSelectInput(
inputId = ns("plot_checks"),
selected = 1,
label = "Select checks to plot",
label = i18n$t("Select checks to plot"),
choices = names,
multiple = TRUE
)
@ -7946,7 +8324,7 @@ regression_server <- function(id,
if (!is.null(rv$list$regression$tables)) {
p <- rv$check_plot() +
# patchwork::wrap_plots() +
patchwork::plot_annotation(title = "Multivariable regression model checks")
patchwork::plot_annotation(title = i18n$t("Multivariable regression model checks"))
layout <- sapply(seq_len(length(p)), \(.x){
@ -8325,7 +8703,7 @@ ui_elements <- function(selection) {
# ),
shiny::selectInput(
inputId = "source",
label="",
label = "",
selected = "file",
choices = "file",
width = "100%"
@ -8361,7 +8739,11 @@ ui_elements <- function(selection) {
),
shiny::conditionalPanel(
condition = "input.source=='env'",
import_globalenv_ui(id = "env", title = NULL)
import_globalenv_ui(
id = "env",
title = NULL,
packages = c("NHANES", "stRoke")
)
),
# shiny::conditionalPanel(
# condition = "input.source=='redcap'",
@ -8615,7 +8997,7 @@ ui_elements <- function(selection) {
sidebar = bslib::sidebar(
shiny::uiOutput(outputId = "data_info_nochar", inline = TRUE),
bslib::accordion(
id="acc_chars",
id = "acc_chars",
open = "acc_chars",
multiple = FALSE,
bslib::accordion_panel(
@ -8661,7 +9043,7 @@ ui_elements <- function(selection) {
sidebar = bslib::sidebar(
# shiny::uiOutput(outputId = "data_info_nochar", inline = TRUE),
bslib::accordion(
id="acc_cor",
id = "acc_cor",
open = "acc_chars",
multiple = FALSE,
bslib::accordion_panel(
@ -10979,6 +11361,7 @@ ui <- bslib::page_fixed(
## Code formatting dependencies
prismDependencies,
prismRDependency,
html_dependency_FreesearchR(),
## Version dependent header
header_include(),
## This adds the actual favicon
@ -11264,7 +11647,8 @@ server <- function(input, output, session) {
rv$code <- modifyList(x = rv$code, list(import = from_redcap$code()))
})
from_env <- datamods::import_globalenv_server(
# from_env <- datamods::import_globalenv_server(
from_env <- import_globalenv_server(
id = "env",
trigger_return = "change",
btn_show_data = FALSE,