bumped to 25.2.1 - new visuals tab - all functions in place - code cleanup has started

This commit is contained in:
Andreas Gammelgaard Damsbo 2025-02-25 09:51:42 +01:00
commit 14edce9912
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36 changed files with 3564 additions and 2976 deletions

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app_version <- function()'250207_1709'
app_version <- function()'250225_0948'

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R/columnSelectInput.R Normal file
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#' A selectizeInput customized for data frames with column labels
#'
#' @description
#' Copied and modified from the IDEAFilter package
#' Adds the option to select "none" which is handled later
#'
#' @param inputId passed to \code{\link[shiny]{selectizeInput}}
#' @param label passed to \code{\link[shiny]{selectizeInput}}
#' @param data \code{data.frame} object from which fields should be populated
#' @param selected default selection
#' @param ... passed to \code{\link[shiny]{selectizeInput}}
#' @param col_subset a \code{vector} containing the list of allowable columns to select
#' @param placeholder passed to \code{\link[shiny]{selectizeInput}} options
#' @param onInitialize passed to \code{\link[shiny]{selectizeInput}} options
#' @param none_label label for "none" item
#'
#' @return a \code{\link[shiny]{selectizeInput}} dropdown element
#'
#' @importFrom shiny selectizeInput
#' @keywords internal
#'
columnSelectInput <- function(inputId, label, data, selected = "", ...,
col_subset = NULL, placeholder = "", onInitialize, none_label="No variable selected") {
datar <- if (is.reactive(data)) data else reactive(data)
col_subsetr <- if (is.reactive(col_subset)) col_subset else reactive(col_subset)
labels <- Map(function(col) {
json <- sprintf(
IDEAFilter:::strip_leading_ws('
{
"name": "%s",
"label": "%s",
"datatype": "%s"
}'),
col,
attr(datar()[[col]], "label") %||% "",
IDEAFilter:::get_dataFilter_class(datar()[[col]])
)
}, col = names(datar()))
if (!"none" %in% names(datar())){
labels <- c("none"=list(sprintf('\n {\n \"name\": \"none\",\n \"label\": \"%s\",\n \"datatype\": \"\"\n }',none_label)),labels)
choices <- setNames(names(labels), labels)
choices <- choices[match(if (length(col_subsetr()) == 0 || isTRUE(col_subsetr() == "")) names(datar()) else col_subsetr(), choices)]
} else {
choices <- setNames(names(datar()), labels)
choices <- choices[match(if (length(col_subsetr()) == 0 || isTRUE(col_subsetr() == "")) choices else col_subsetr(), choices)]
}
shiny::selectizeInput(
inputId = inputId,
label = label,
choices = choices,
selected = selected,
...,
options = c(
list(render = I("{
// format the way that options are rendered
option: function(item, escape) {
item.data = JSON.parse(item.label);
return '<div style=\"padding: 3px 12px\">' +
'<div><strong>' +
escape(item.data.name) + ' ' +
'<span style=\"opacity: 0.3;\"><code style=\"color: black;\"> ' +
item.data.datatype +
'</code></span>' +
'</strong></div>' +
(item.data.label != '' ? '<div style=\"line-height: 1em;\"><small>' + escape(item.data.label) + '</small></div>' : '') +
'</div>';
},
// avoid data vomit splashing on screen when an option is selected
item: function(item, escape) {
item.data = JSON.parse(item.label);
return '<div>' +
escape(item.data.name) +
'</div>';
}
}"))
)
)
}

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R/contrast_text.R Normal file
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#' @title Contrast Text Color
#' @description Calculates the best contrast text color for a given
#' background color.
#' @param background A hex/named color value that represents the background.
#' @param light_text A hex/named color value that represents the light text
#' color.
#' @param dark_text A hex/named color value that represents the dark text color.
#' @param threshold A numeric value between 0 and 1 that is used to determine
#' the luminance threshold of the background color for text color.
#' @param method A character string that specifies the method for calculating
#' the luminance. Three different methods are available:
#' c("relative","perceived","perceived_2")
#' @param ... parameter overflow. Ignored.
#' @details
#' This function aids in deciding the font color to print on a given background.
#' The function is based on the example provided by teppo:
#' https://stackoverflow.com/a/66669838/21019325.
#' The different methods provided are based on the methods outlined in the
#' StackOverflow thread:
#' https://stackoverflow.com/questions/596216/formula-to-determine-perceived-brightness-of-rgb-color
#' @return A character string that contains the best contrast text color.
#' @examples
#' contrast_text(c("#F2F2F2", "blue"))
#'
#' contrast_text(c("#F2F2F2", "blue"), method="relative")
#' @export
#'
#' @importFrom grDevices col2rgb
#'
contrast_text <- function(background,
light_text = 'white',
dark_text = 'black',
threshold = 0.5,
method = "perceived_2",
...) {
if (method == "relative") {
luminance <-
c(c(.2126, .7152, .0722) %*% grDevices::col2rgb(background) / 255)
} else if (method == "perceived") {
luminance <-
c(c(.299, .587, .114) %*% grDevices::col2rgb(background) / 255)
} else if (method == "perceived_2") {
luminance <- c(sqrt(colSums((
c(.299, .587, .114) * grDevices::col2rgb(background)
) ^ 2)) / 255)
}
ifelse(luminance < threshold,
light_text,
dark_text)
}

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R/data_plots.R Normal file
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# source(here::here("functions.R"))
#' Data correlations evaluation module
#'
#' @param id Module id. (Use 'ns("id")')
#'
#' @name data-correlations
#' @returns Shiny ui module
#' @export
#'
data_visuals_ui <- function(id, tab_title="Plots", ...) {
ns <- shiny::NS(id)
# bslib::navset_bar(
list(
# Sidebar with a slider input
sidebar = bslib::sidebar(
bslib::accordion(
multiple = FALSE,
bslib::accordion_panel(
title = "Creating plot",
icon = bsicons::bs_icon("graph-up"),
shiny::uiOutput(outputId = ns("primary")),
shiny::uiOutput(outputId = ns("type")),
shiny::uiOutput(outputId = ns("secondary")),
shiny::uiOutput(outputId = ns("tertiary"))
),
bslib::accordion_panel(
title = "Advanced",
icon = bsicons::bs_icon("gear")
),
bslib::accordion_panel(
title = "Download",
icon = bsicons::bs_icon("download"),
shinyWidgets::noUiSliderInput(
inputId = ns("height"),
label = "Plot height (mm)",
min = 50,
max = 300,
value = 100,
step = 1,
format = shinyWidgets::wNumbFormat(decimals=0),
color = datamods:::get_primary_color()
),
shinyWidgets::noUiSliderInput(
inputId = ns("width"),
label = "Plot width (mm)",
min = 50,
max = 300,
value = 100,
step = 1,
format = shinyWidgets::wNumbFormat(decimals=0),
color = datamods:::get_primary_color()
),
shiny::selectInput(
inputId = ns("plot_type"),
label = "File format",
choices = list(
"png",
"tiff",
"eps",
"pdf",
"jpeg",
"svg"
)
),
shiny::br(),
# Button
shiny::downloadButton(
outputId = ns("download_plot"),
label = "Download plot",
icon = shiny::icon("download")
)
)
)
),
bslib::nav_panel(
title = tab_title,
shiny::plotOutput(ns("plot"))
)
)
}
#'
#' @param data data
#' @param ... ignored
#'
#' @name data-correlations
#' @returns shiny server module
#' @export
data_visuals_server <- function(id,
data,
...) {
shiny::moduleServer(
id = id,
module = function(input, output, session) {
ns <- session$ns
rv <- shiny::reactiveValues(
plot.params = NULL,
plot = NULL
)
output$primary <- shiny::renderUI({
columnSelectInput(
inputId = ns("primary"),
data = data,
placeholder = "Select variable",
label = "Response variable",
multiple = FALSE
)
})
output$type <- shiny::renderUI({
shiny::req(input$primary)
# browser()
if (!input$primary %in% names(data())) {
plot_data <- data()[1]
} else {
plot_data <- data()[input$primary]
}
plots <- possible_plots(
data = plot_data
)
shiny::selectizeInput(
inputId = ns("type"),
selected = NULL,
label = shiny::h4("Plot type"),
choices = plots,
multiple = FALSE
)
})
rv$plot.params <- shiny::reactive({
get_plot_options(input$type)
})
output$secondary <- shiny::renderUI({
shiny::req(input$type)
# browser()
columnSelectInput(
inputId = ns("secondary"),
data = data,
placeholder = "Select variable",
label = "Secondary/group variable",
multiple = FALSE,
col_subset = c(
purrr::pluck(rv$plot.params(), 1)[["secondary.extra"]],
all_but(
colnames(subset_types(
data(),
purrr::pluck(rv$plot.params(), 1)[["secondary.type"]]
)),
input$primary
)
),
none_label = "No variable"
)
})
output$tertiary <- shiny::renderUI({
shiny::req(input$type)
columnSelectInput(
inputId = ns("tertiary"),
data = data,
placeholder = "Select variable",
label = "Strata variable",
multiple = FALSE,
col_subset = c(
"none",
all_but(
colnames(subset_types(
data(),
purrr::pluck(rv$plot.params(), 1)[["tertiary.type"]]
)),
input$primary,
input$secondary
)
),
none_label = "No stratification"
)
})
rv$plot <- shiny::reactive({
shiny::req(input$primary)
shiny::req(input$type)
shiny::req(input$secondary)
shiny::req(input$tertiary)
create_plot(
data = data(),
type = names(rv$plot.params()),
x = input$primary,
y = input$secondary,
z = input$tertiary
)
})
output$plot <- shiny::renderPlot({
rv$plot()
})
output$download_plot <- shiny::downloadHandler(
filename = shiny::reactive({
paste0("plot.", input$plot_type)
}),
content = function(file) {
shiny::withProgress(message = "Drawing the plot. Hold on for a moment..", {
ggplot2::ggsave(filename = file,
plot = rv$plot(),
width = input$width,
height = input$height,
dpi = 300,
units = "mm",scale = 2)
})
}
)
shiny::observe(
return(rv$plot)
)
}
)
}
#' Select all from vector but
#'
#' @param data vector
#' @param ... exclude
#'
#' @returns
#' @export
#'
#' @examples
#' all_but(1:10, c(2, 3), 11, 5)
all_but <- function(data, ...) {
data[!data %in% c(...)]
}
#' Easily subset by data type function
#'
#' @param data data
#' @param types desired types
#' @param type.fun function to get type. Default is outcome_type
#'
#' @returns
#' @export
#'
#' @examples
#' default_parsing(mtcars) |> subset_types("ordinal")
#' default_parsing(mtcars) |> subset_types(c("dichotomous", "ordinal"))
#' #' default_parsing(mtcars) |> subset_types("factor",class)
subset_types <- function(data, types, type.fun = outcome_type) {
data[sapply(data, type.fun) %in% types]
}
#' Implemented functions
#'
#' @description
#' Library of supported functions. The list name and "descr" element should be
#' unique for each element on list.
#'
#' - descr: Plot description
#'
#' - primary.type: Primary variable data type (continuous, dichotomous or ordinal)
#'
#' - secondary.type: Secondary variable data type (continuous, dichotomous or ordinal)
#'
#' - secondary.extra: "none" or NULL to have option to choose none.
#'
#' - tertiary.type: Tertiary variable data type (continuous, dichotomous or ordinal)
#'
#'
#' @returns list
#' @export
#'
#' @examples
#' supported_plots() |> str()
supported_plots <- function() {
list(
plot_hbars = list(
descr = "Stacked horizontal bars (Grotta bars)",
primary.type = c("dichotomous", "ordinal"),
secondary.type = c("dichotomous", "ordinal"),
tertiary.type = c("dichotomous", "ordinal"),
secondary.extra = "none"
),
plot_violin = list(
descr = "Violin plot",
primary.type = c("continuous", "dichotomous", "ordinal"),
secondary.type = c("dichotomous", "ordinal"),
tertiary.type = c("dichotomous", "ordinal"),
secondary.extra = "none"
),
plot_ridge = list(
descr = "Ridge plot",
primary.type = "continuous",
secondary.type = c("dichotomous", "ordinal"),
tertiary.type = c("dichotomous", "ordinal"),
secondary.extra = NULL
),
plot_scatter = list(
descr = "Scatter plot",
primary.type = "continuous",
secondary.type = c("continuous", "ordinal"),
tertiary.type = c("dichotomous", "ordinal"),
secondary.extra = NULL
)
)
}
#' Title
#'
#' @returns
#' @export
#'
#' @examples
#' mtcars |>
#' default_parsing() |>
#' plot_ridge(x = "mpg", y = "cyl")
#' mtcars |> plot_ridge(x = "mpg", y = "cyl", z = "gear")
plot_ridge <- function(data, x, y, z = NULL, ...) {
if (!is.null(z)) {
ds <- split(data, data[z])
} else {
ds <- list(data)
}
out <- lapply(ds, \(.ds){
ggplot2::ggplot(.ds, ggplot2::aes(x = !!dplyr::sym(x), y = !!dplyr::sym(y), fill = !!dplyr::sym(y))) +
ggridges::geom_density_ridges() +
ggridges::theme_ridges() +
ggplot2::theme(legend.position = "none") |> rempsyc:::theme_apa()
})
patchwork::wrap_plots(out)
}
#' Get possible regression models
#'
#' @param data data
#'
#' @returns character vector
#' @export
#'
#' @examples
#' mtcars |>
#' default_parsing() |>
#' dplyr::pull("cyl") |>
#' possible_plots()
#'
#' mtcars |>
#' default_parsing() |>
#' dplyr::select("mpg") |>
#' possible_plots()
possible_plots <- function(data) {
# browser()
if (is.data.frame(data)) {
data <- data[[1]]
}
type <- outcome_type(data)
if (type == "unknown") {
out <- type
} else {
out <- supported_plots() |>
lapply(\(.x){
if (type %in% .x$primary.type) {
.x$descr
}
}) |>
unlist()
}
unname(out)
}
#' Get the function options based on the selected function description
#'
#' @param data vector
#'
#' @returns list
#' @export
#'
#' @examples
#' ls <- mtcars |>
#' default_parsing() |>
#' dplyr::pull(mpg) |>
#' possible_plots() |>
#' (\(.x){
#' .x[[1]]
#' })() |>
#' get_plot_options()
get_plot_options <- function(data) {
descrs <- supported_plots() |>
lapply(\(.x){
.x$descr
}) |>
unlist()
supported_plots() |>
(\(.x){
.x[match(data, descrs)]
})()
}
#' Wrapper to create plot based on provided type
#'
#' @param type plot type (derived from possible_plots() and matches custom function)
#' @param ... ignored for now
#'
#' @returns
#' @export
#'
#' @examples
#' create_plot(mtcars, "plot_violin", "mpg", "cyl")
create_plot <- function(data, type, x, y, z = NULL, ...) {
if (!y %in% names(data)) {
y <- NULL
}
if (!z %in% names(data)) {
z <- NULL
}
do.call(
type,
list(data, x, y, z, ...)
)
}
#' Nice horizontal stacked bars (Grotta bars)
#'
#' @returns ggplot2 object
#' @export
#'
#' @examples
#' mtcars |> plot_hbars(x = "carb", y = "cyl")
#' mtcars |> plot_hbars(x = "carb", y = NULL)
plot_hbars <- function(data, x, y, z = NULL) {
out <- vertical_stacked_bars(data = data, score = x, group = y, strata = z)
out
}
#' Vertical stacked bar plot wrapper
#'
#' @param data
#' @param score
#' @param group
#' @param strata
#' @param t.size
#'
#' @return
#' @export
#'
vertical_stacked_bars <- function(data,
score = "full_score",
group = "pase_0_q",
strata = NULL,
t.size = 10,
l.color = "black",
l.size = .5,
draw.lines = TRUE) {
if (is.null(group)) {
df.table <- data[c(score, group, strata)] |>
dplyr::mutate("All" = 1) |>
table()
group <- "All"
draw.lines <- FALSE
} else {
df.table <- data[c(score, group, strata)] |>
table()
}
p <- df.table |>
rankinPlot::grottaBar(
scoreName = score,
groupName = group,
textColor = c("black", "white"),
strataName = strata,
textCut = 6,
textSize = 20,
printNumbers = "none",
lineSize = l.size,
returnData = TRUE
)
colors <- viridisLite::viridis(nrow(df.table))
contrast_cut <-
sum(contrast_text(colors, threshold = .3) == "white")
score_label <- ifelse(is.na(REDCapCAST::get_attr(data$score, "label")), score, REDCapCAST::get_attr(data$score, "label"))
group_label <- ifelse(is.na(REDCapCAST::get_attr(data$group, "label")), group, REDCapCAST::get_attr(data$group, "label"))
p |>
(\(.x){
.x$plot +
ggplot2::geom_text(
data = .x$rectData[which(.x$rectData$n >
0), ],
size = t.size,
fontface = "plain",
ggplot2::aes(
x = group,
y = p_prev + 0.49 * p,
color = as.numeric(score) > contrast_cut,
# label = paste0(sprintf("%2.0f", 100 * p),"%"),
label = sprintf("%2.0f", 100 * p)
)
) +
ggplot2::labs(fill = score_label) +
ggplot2::scale_fill_manual(values = rev(colors)) +
ggplot2::theme(
legend.position = "bottom",
axis.title = ggplot2::element_text(),
) +
ggplot2::xlab(group_label) +
ggplot2::ylab(NULL)
# viridis::scale_fill_viridis(discrete = TRUE, direction = -1, option = "D")
})()
}
#' Print label, and if missing print variable name
#'
#' @param data vector or data frame
#'
#' @returns character string
#' @export
#'
#' @examples
#' mtcars |> get_label(var = "mpg")
#' mtcars$mpg |> get_label()
#' gtsummary::trial |> get_label(var = "trt")
#' 1:10 |> get_label()
get_label <- function(data, var = NULL) {
if (!is.null(var)) {
data <- data[[var]]
}
out <- REDCapCAST::get_attr(data = data, attr = "label")
if (is.na(out)) {
if (is.null(var)) {
out <- deparse(substitute(data))
} else {
out <- gsub('\"', "", deparse(substitute(var)))
}
}
out
}
#' Beatiful violin plot
#'
#' @returns ggplot2 object
#' @export
#'
#' @examples
#' mtcars |> plot_violin(x = "mpg", y = "cyl", z = "gear")
plot_violin <- function(data, x, y, z = NULL) {
if (!is.null(z)) {
ds <- split(data, data[z])
} else {
ds <- list(data)
}
out <- lapply(ds, \(.ds){
rempsyc::nice_violin(
data = .ds,
group = y,
response = x, xtitle = get_label(data, var = x), ytitle = get_label(data, var = y)
)
})
patchwork::wrap_plots(out)
}
#' Beatiful violin plot
#'
#' @returns ggplot2 object
#' @export
#'
#' @examples
#' mtcars |> plot_scatter(x = "mpg", y = "wt")
plot_scatter <- function(data, x, y, z = NULL) {
if (is.null(z)) {
rempsyc::nice_scatter(
data = data,
predictor = y,
response = x, xtitle = get_label(data, var = x), ytitle = get_label(data, var = y)
)
} else {
rempsyc::nice_scatter(
data = data,
predictor = y,
response = x,
group = z
)
}
}

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@ -95,31 +95,31 @@ file_app <- function() {
file_app()
tdm_data_upload <- teal::teal_data_module(
ui <- function(id) {
shiny::fluidPage(
m_datafileUI(id)
)
},
server = function(id) {
m_datafileServer(id, output.format = "teal")
}
)
tdm_data_read <- teal::teal_data_module(
ui <- function(id) {
shiny::fluidPage(
m_redcap_readUI(id = "redcap")
)
},
server = function(id) {
moduleServer(
id,
function(input, output, session) {
ns <- session$ns
m_redcap_readServer(id = "redcap", output.format = "teal")
}
)
}
)
# tdm_data_upload <- teal::teal_data_module(
# ui <- function(id) {
# shiny::fluidPage(
# m_datafileUI(id)
# )
# },
# server = function(id) {
# m_datafileServer(id, output.format = "teal")
# }
# )
#
# tdm_data_read <- teal::teal_data_module(
# ui <- function(id) {
# shiny::fluidPage(
# m_redcap_readUI(id = "redcap")
# )
# },
# server = function(id) {
# moduleServer(
# id,
# function(input, output, session) {
# ns <- session$ns
#
# m_redcap_readServer(id = "redcap", output.format = "teal")
# }
# )
# }
# )

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@ -266,3 +266,29 @@ remove_empty_cols <- function(data,cutoff=.7){
}) >= cutoff
data[filter]
}
#' Append list with named index
#'
#' @param data data to add to list
#' @param list list
#' @param index index name
#'
#' @returns list
#'
#' @examples
#' 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){
## This will overwrite and not warn
## Not very safe, but convenient to append code to list
if (index %in% names(list)){
list[[index]] <- data
out <- list
} else {
out <- setNames(c(list,list(data)),c(names(list),index))
}
out
}

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@ -271,19 +271,19 @@ m_redcap_readServer <- function(id, output.format = c("df", "teal", "list")) {
)
}
#' REDCap import teal data module
#'
#' @rdname redcap_read_shiny_module
tdm_redcap_read <- teal::teal_data_module(
ui <- function(id) {
shiny::fluidPage(
m_redcap_readUI(id)
)
},
server = function(id) {
m_redcap_readServer(id, output.format = "teal")
}
)
# #' REDCap import teal data module
# #'
# #' @rdname redcap_read_shiny_module
# tdm_redcap_read <- teal::teal_data_module(
# ui <- function(id) {
# shiny::fluidPage(
# m_redcap_readUI(id)
# )
# },
# server = function(id) {
# m_redcap_readServer(id, output.format = "teal")
# }
# )
#' Test app for the redcap_read_shiny_module

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@ -15,7 +15,7 @@
#' shiny_freesearcheR(launch.browser = TRUE)
#' }
shiny_freesearcheR <- function(...) {
appDir <- system.file("apps", "data_analysis_modules", package = "freesearcheR")
appDir <- system.file("apps", "freesearcheR", package = "freesearcheR")
if (appDir == "") {
stop("Could not find the app directory. Try re-installing `freesearcheR`.", call. = FALSE)
}

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R/update-factor-ext.R Normal file
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## Works, but not implemented
##
## These edits mainly allows for
#' @title Module to Reorder the Levels of a Factor Variable
#'
#' @description
#' This module contain an interface to reorder the levels of a factor variable.
#'
#'
#' @param id Module ID.
#'
#' @return A [shiny::reactive()] function returning the data.
#' @export
#'
#' @importFrom shiny NS fluidRow tagList column actionButton
#' @importFrom shinyWidgets virtualSelectInput prettyCheckbox
#' @importFrom toastui datagridOutput
#' @importFrom htmltools tags
#'
#' @name update-factor
#'
#' @example examples/update_factor.R
update_factor_ui <- function(id) {
ns <- NS(id)
tagList(
tags$style(
".tui-grid-row-header-draggable span {width: 3px !important; height: 3px !important;}"
),
fluidRow(
column(
width = 6,
virtualSelectInput(
inputId = ns("variable"),
label = i18n("Factor variable to reorder:"),
choices = NULL,
width = "100%",
zIndex = 50
)
),
column(
width = 3,
class = "d-flex align-items-end",
actionButton(
inputId = ns("sort_levels"),
label = tagList(
ph("sort-ascending"),
i18n("Sort by levels")
),
class = "btn-outline-primary mb-3",
width = "100%"
)
),
column(
width = 3,
class = "d-flex align-items-end",
actionButton(
inputId = ns("sort_occurrences"),
label = tagList(
ph("sort-ascending"),
i18n("Sort by count")
),
class = "btn-outline-primary mb-3",
width = "100%"
)
)
),
datagridOutput(ns("grid")),
tags$div(
class = "float-end",
prettyCheckbox(
inputId = ns("new_var"),
label = i18n("Create a new variable (otherwise replaces the one selected)"),
value = FALSE,
status = "primary",
outline = TRUE,
inline = TRUE
),
actionButton(
inputId = ns("create"),
label = tagList(ph("arrow-clockwise"), i18n("Update factor variable")),
class = "btn-outline-primary"
)
),
tags$div(class = "clearfix")
)
}
#' @param data_r A [shiny::reactive()] function returning a `data.frame`.
#'
#' @export
#'
#' @importFrom shiny moduleServer observeEvent reactive reactiveValues req bindEvent isTruthy updateActionButton
#' @importFrom shinyWidgets updateVirtualSelect
#' @importFrom toastui renderDatagrid datagrid grid_columns grid_colorbar
#'
#' @rdname update-factor
update_factor_server <- function(id, data_r = reactive(NULL)) {
moduleServer(
id,
function(input, output, session) {
rv <- reactiveValues(data = NULL, data_grid = NULL)
bindEvent(observe({
data <- data_r()
rv$data <- data
vars_factor <- vapply(data, is.factor, logical(1))
vars_factor <- names(vars_factor)[vars_factor]
updateVirtualSelect(
inputId = "variable",
choices = vars_factor,
selected = if (isTruthy(input$variable)) input$variable else vars_factor[1]
)
}), data_r(), input$hidden)
observeEvent(input$variable, {
data <- req(data_r())
variable <- req(input$variable)
grid <- as.data.frame(table(data[[variable]]))
rv$data_grid <- grid
})
observeEvent(input$sort_levels, {
if (input$sort_levels %% 2 == 1) {
decreasing <- FALSE
label <- tagList(
ph("sort-descending"),
"Sort Levels"
)
} else {
decreasing <- TRUE
label <- tagList(
ph("sort-ascending"),
"Sort Levels"
)
}
updateActionButton(inputId = "sort_levels", label = as.character(label))
rv$data_grid <- rv$data_grid[order(rv$data_grid[[1]], decreasing = decreasing), ]
})
observeEvent(input$sort_occurrences, {
if (input$sort_occurrences %% 2 == 1) {
decreasing <- FALSE
label <- tagList(
ph("sort-descending"),
i18n("Sort count")
)
} else {
decreasing <- TRUE
label <- tagList(
ph("sort-ascending"),
i18n("Sort count")
)
}
updateActionButton(inputId = "sort_occurrences", label = as.character(label))
rv$data_grid <- rv$data_grid[order(rv$data_grid[[2]], decreasing = decreasing), ]
})
output$grid <- renderDatagrid({
req(rv$data_grid)
gridTheme <- getOption("datagrid.theme")
if (length(gridTheme) < 1) {
datamods:::apply_grid_theme()
}
on.exit(toastui::reset_grid_theme())
data <- rv$data_grid
data <- add_var_toset(data, "Var1", "New label")
grid <- datagrid(
data = data,
draggable = TRUE,
sortable = FALSE,
data_as_input = TRUE
)
grid <- grid_columns(
grid,
columns = c("Var1", "Var1_toset", "Freq"),
header = c(i18n("Levels"), "New label", i18n("Count"))
)
grid <- grid_colorbar(
grid,
column = "Freq",
label_outside = TRUE,
label_width = "30px",
background = "#D8DEE9",
bar_bg = datamods:::get_primary_color(),
from = c(0, max(rv$data_grid$Freq) + 1)
)
grid <- toastui::grid_style_column(
grid = grid,
column = "Var1_toset",
fontStyle = "italic"
)
grid <- toastui::grid_editor(
grid = grid,
column = "Var1_toset",
type = "text"
)
grid
})
data_updated_r <- reactive({
data <- req(data_r())
variable <- req(input$variable)
grid <- req(input$grid_data)
name_var <- if (isTRUE(input$new_var)) {
paste0(variable, "_updated")
} else {
variable
}
data[[name_var]] <- factor(
as.character(data[[variable]]),
levels = grid[["Var1"]]
)
data[[name_var]] <- factor(
data[[variable]],
labels = ifelse(grid[["Var1_toset"]]=="New label",grid[["Var1"]],grid[["Var1_toset"]])
)
data
})
data_returned_r <- observeEvent(input$create, {
rv$data <- data_updated_r()
})
return(reactive(rv$data))
}
)
}
#' @inheritParams shiny::modalDialog
#' @export
#'
#' @importFrom shiny showModal modalDialog textInput
#' @importFrom htmltools tagList
#'
#' @rdname update-factor
modal_update_factor <- function(id,
title = i18n("Update levels of a factor"),
easyClose = TRUE,
size = "l",
footer = NULL) {
ns <- NS(id)
showModal(modalDialog(
title = tagList(title, datamods:::button_close_modal()),
update_factor_ui(id),
tags$div(
style = "display: none;",
textInput(inputId = ns("hidden"), label = NULL, value = datamods:::genId())
),
easyClose = easyClose,
size = size,
footer = footer
))
}
#' @inheritParams shinyWidgets::WinBox
#' @export
#'
#' @importFrom shinyWidgets WinBox wbOptions wbControls
#' @importFrom htmltools tagList
#' @rdname create-column
winbox_update_factor <- function(id,
title = i18n("Update levels of a factor"),
options = shinyWidgets::wbOptions(),
controls = shinyWidgets::wbControls()) {
ns <- NS(id)
WinBox(
title = title,
ui = tagList(
update_factor_ui(id),
tags$div(
style = "display: none;",
textInput(inputId = ns("hidden"), label = NULL, value = genId())
)
),
options = modifyList(
shinyWidgets::wbOptions(height = "615px", modal = TRUE),
options
),
controls = controls,
auto_height = FALSE
)
}

View file

@ -367,8 +367,8 @@ summary_vars <- function(data) {
name = names(data),
label = lapply(data, \(.x) REDCapCAST::get_attr(.x, "label")) |> unlist(),
class = get_classes(data),
# n_missing = unname(colSums(is.na(data))),
# p_complete = 1 - n_missing / nrow(data),
n_missing = unname(colSums(is.na(data))),
p_complete = 1 - n_missing / nrow(data),
n_unique = get_n_unique(data)
)
@ -440,11 +440,11 @@ update_variables_datagrid <- function(data, height = NULL, selectionId = NULL, b
minWidth = 100
)
# grid <- toastui::grid_format(
# grid = grid,
# "p_complete",
# formatter = toastui::JS("function(obj) {return (obj.value*100).toFixed(0) + '%';}")
# )
grid <- toastui::grid_format(
grid = grid,
"p_complete",
formatter = toastui::JS("function(obj) {return (obj.value*100).toFixed(0) + '%';}")
)
grid <- toastui::grid_style_column(
grid = grid,
column = "name_toset",