493 FilteredDatasetDefault class
#497
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averissimo
previously requested changes
Dec 12, 2023
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Tried using it with a teal app (see below) and it fails due to not having implemented method ui_add on FilteredDatasetDefault
This works for me, although the message needs to be something else 😅
diff --git a/R/FilteredDatasetDefault.R b/R/FilteredDatasetDefault.R
index 5419cb45..0fced5dc 100644
--- a/R/FilteredDatasetDefault.R
+++ b/R/FilteredDatasetDefault.R
@@ -46,6 +46,21 @@ DefaultFilteredDataset <- R6::R6Class( # nolint
sprintf(" - unfiltered dataset:\t\"%s\": %s", private$dataname, class_string)
},
+ #' @description
+ #' UI module to add filter variable for this dataset
+ #'
+ #' UI module to add filter variable for this dataset
+ #' @param id (`character(1)`)\cr
+ #' identifier of the element - preferably containing dataset name
+ #'
+ #' @return function - shiny UI module
+ ui_add = function(id) {
+ ns <- NS(id)
+ tagList(
+ div("I'm not a real filter")
+ )
+ },
+Below is the sample app
Expand sample code
library(teal)
td <- teal_data(
new_iris = transform(iris, id = seq_len(nrow(iris))),
code = "
new_iris <- transform(iris, id = seq_len(nrow(iris)))
"
) |> within({
aa <- 1:10
})
datanames(td) <- c(datanames(td), "aa")
app <- init(
data = td,
modules = modules(
example_module(label = "example teal module")
),
title = "App title"
) |> shiny::runApp()
Co-authored-by: André Veríssimo <[email protected]> Signed-off-by: Aleksander Chlebowski <[email protected]>
…engineering/teal.slice into 493_FilteredDatasetDefault@main
|
That's quite a lot of warnings. Perhaps we should reconsider @gogonzo? |
gogonzo
reviewed
Dec 14, 2023
gogonzo
reviewed
Dec 14, 2023
|
@pawelru @lcd2yyz @donyunardi @danielinteractive It is official. options(teal.log_level = "TRACE", teal.show_js_log = TRUE, teal.bs_theme = bslib::bs_theme(version = 3))
library(shiny)
library(teal)
data <- teal_data() |>
within({
set.seed(1)
library(scda)
library(airway)
library(MultiAssayExperiment)
data(miniACC, envir = environment())
data(airway, envir = environment())
any_variable <- "elo"
ADSL <- synthetic_cdisc_data("latest")$adsl
ADSL$categorical <- sample(letters[1:3], size = nrow(ADSL), replace = TRUE, prob = c(.1, .3, .6))
ADTTE <- synthetic_cdisc_data("latest")$adtte
ADRS <- synthetic_cdisc_data("latest")$adrs
})
datanames(data) <- c("ADSL", "ADTTE", "ADRS", "airway", "miniACC", "any_variable")
join_keys(data) <- default_cdisc_join_keys[c("ADSL", "ADTTE", "ADRS")]
default_filters <- teal.slice::teal_slices(
teal_slice(dataname = "ADSL", varname = "categorical", selected = c("a"), id = "categorical", multiple = FALSE),
teal_slice(id = "SE", title = "Safety-Evaluable", dataname = "ADSL", expr = "SAFFL == 'Y'"),
teal_slice(dataname = "miniACC", varname = "years_to_birth", selected = c(30, 50), keep_na = TRUE, keep_inf = FALSE),
teal_slice(dataname = "miniACC", varname = "gender", selected = "female", keep_na = TRUE),
teal_slice(dataname = "miniACC", varname = "ARRAY_TYPE", selected = "protein_level", experiment = "RPPAArray", arg = "subset"),
teal_slice(dataname = "airway", varname = "cell", selected = "N61311", experiment = "RNASeq"), # ignored
teal_slice(dataname = "miniACC", varname = "Genes", selected = "G6PD", experiment = "RPPAArray", arg = "subset"),
count_type = "none"
)
app <- init(
data = data,
modules = modules(
modules(
label = "tab1",
example_module("funny"),
example_module("funny", datanames = "airway"),
example_module("funny2", datanames = "ADTTE"), # will limit datanames to ADTTE and ADSL (parent),
teal.modules.general::tm_data_table(datasets_selected = c("ADSL", "ADTTE", "ADRS"))
)
),
filter = default_filters
)
runApp(app)
|
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Closes #493
Renamed class
DefaultFilteredDatasettoDataframeFilteredDataset.Created new class
DefaultFilteredDataset.Renamed S3 methods for
init_filteredDatasetaccordingly.Removed assertion on dataset type in
FilteredData$set_dataset.New class
DefaultFilteredDatasetonly has the following methods:$initialize: initiates object$format: returns string stating " - unfiltered dataset: : ", trims class to 37 chars by default$get_call: returnsNULL$get_filter state: returnsNULL$set_filter_state: returnsNULLwith warning$clear_filter_states: returnsNULL$get_filter_overview: returnsNULL$ui_active: displays emptydiv$ui_add: displays emptydiv$get_filter_overview: returns 1x3data.framewith dataset name and two NAs in its only rowFilteredData$get_filter_overviewputs the "all-NA" overviews at the bottom of the list.FilteredData$srv_overviewdisplays names of unfiltered datasets with warning icon that has a popover explaining that the data set in question is of an unsupported class.