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Reduce unwanted reactivity on filter panel changes #593

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Reduce unwanted reactivity on filter panel changes #593

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5b322a8
feat: react only when the filter call changes
vedhav May 23, 2024
89572a4
fix: suppress reactivity for CDISC child datasets too
vedhav May 24, 2024
4c4b081
chore: moving the observer to constructor
vedhav May 24, 2024
4c507ca
Revert "chore: moving the observer to constructor"
vedhav May 24, 2024
3ab89db
Merge branch 'main' into 62-improve-reactivity@main
donyunardi Jun 26, 2024
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2 changes: 1 addition & 1 deletion R/FilterStates.R
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Original file line number Diff line number Diff line change
Expand Up @@ -729,7 +729,7 @@ FilterStates <- R6::R6Class( # nolint
# create a new FilterState
fstate <- init_filter_state(
x = data[, slice$varname, drop = TRUE],
# data_reactive is a function which eventually calls get_call(sid).
# data_reactive is a function which eventually depends on the reactiveVal reactive_call().
# This chain of calls returns column from the data filtered by everything
# but filter identified by the sid argument. FilterState then get x_reactive
# and this no longer needs to be a function to pass sid. reactive in the FilterState
Expand Down
8 changes: 7 additions & 1 deletion R/FilteredDataset.R
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Expand Up @@ -42,6 +42,7 @@ FilteredDataset <- R6::R6Class( # nolint
private$dataname <- dataname
private$keys <- keys
private$label <- if (is.null(label)) character(0) else label
private$reactive_call <- reactiveVal()

# function executing reactive call and returning data
private$data_filtered_fun <- function(sid = "") {
Expand All @@ -53,7 +54,7 @@ FilteredDataset <- R6::R6Class( # nolint
}
env <- new.env(parent = parent.env(globalenv()))
env[[dataname]] <- private$dataset
filter_call <- self$get_call(sid)
filter_call <- private$reactive_call()
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It won't work for filter-counts which has non-empty sid as an argument. Let me explain briefly how sid works and why you can't cache these object in FilteredDataset.

For given FilterState(s) configuration there are two kind of calls (and data) produced in the same time. When the filter is modified possibly multiple calls of data_filtered_fun are invoked. This means that this can't be cached here because this function needs to be called several times with different sid.

  1. All FilterState are combined into one call and it is returned to the module. For this case your current solution works just perfect
image
  1. reactive counts in a single (each) FilterState are calculated on data filtered by every filter but not "this" filter.
image

Why are counts so weird?
When you filter single column you'd like to still see the counts of the unfiltered ranges. If we don't show these counts user wouldn't know how many observations are outside of the filtered range.

correct incorrect

Even more technical explaination here

example app 
# options(teal.log_level = "TRACE", teal.show_js_log = TRUE)
library("teal.slice")
library(teal)
library(scda)
library(SummarizedExperiment)

data <- teal_data() |> within({
  # MAE <- hermes::multi_assay_experiment
  ADSL <- synthetic_cdisc_data("latest")$adsl
  ADSL$empty <- NA
  ADSL$logical1 <- FALSE
  ADSL$logical <- sample(c(TRUE, FALSE), size = nrow(ADSL), replace = TRUE)
  ADSL$numeric <- rnorm(nrow(ADSL))
  ADSL$categorical <- sample(letters[1:10], size = nrow(ADSL), replace = TRUE)
  ADSL$date <- Sys.Date() + seq_len(nrow(ADSL))
  ADSL$datetime <- Sys.time() + seq_len(nrow(ADSL)) * 3600 * 12

  ADSL$numeric[sample(1:nrow(ADSL), size = 10, )] <- NA
  ADSL$numeric[sample(1:nrow(ADSL), size = 10, )] <- Inf
  ADSL$logical[sample(1:nrow(ADSL), size = 10, )] <- NA
  ADSL$date[sample(1:nrow(ADSL), size = 10, )] <- NA
  ADSL$datetime[sample(1:nrow(ADSL), size = 10, )] <- NA
  ADSL$categorical[sample(1:nrow(ADSL), size = 10, )] <- NA

  ADTTE <- synthetic_cdisc_data("latest")$adtte
  ADRS <- synthetic_cdisc_data("latest")$adrs
})

teal.data::datanames(data) <- c(
  #  "MAE",
  "ADSL", "ADTTE", "ADRS"
)
teal.data::join_keys(data) <- teal.data::default_cdisc_join_keys[teal.data::datanames(data)]

app <- init(
  data = data,
  modules = list(
    example_module("mod1"),
    modules(
      example_module("mod2")
    )
  ),
  filter = teal_slices(
    teal_slice("ADSL", "numeric", id = "numeric1"),
    teal_slice("ADSL", "numeric", id = "numeric2"),
    module_specific = TRUE,
    mapping = list(
      mod1 = "numeric1",
      mod2 = "numeric2"
    ),
    count_type = "all"
  )
)

runApp(app)

eval_expr_with_msg(filter_call, env)
get(x = dataname, envir = env)
}
Expand Down Expand Up @@ -301,6 +302,10 @@ FilteredDataset <- R6::R6Class( # nolint
}
)

observeEvent(self$get_call(), ignoreNULL = FALSE, {
private$reactive_call(self$get_call())
})

observeEvent(self$get_filter_state(), {
shinyjs::hide("filter_count_ui")
shinyjs::show("filters")
Expand Down Expand Up @@ -374,6 +379,7 @@ FilteredDataset <- R6::R6Class( # nolint
dataname = character(0),
keys = character(0),
label = character(0),
reactive_call = NULL, # reactiveVal

# Adds `FilterStates` to the `private$filter_states`.
# `FilterStates` is added once for each element of the dataset.
Expand Down
2 changes: 1 addition & 1 deletion R/FilteredDatasetDataframe.R
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Expand Up @@ -89,7 +89,7 @@ DataframeFilteredDataset <- R6::R6Class( # nolint
env <- new.env(parent = parent.env(globalenv()))
env[[dataname]] <- private$dataset
env[[parent_name]] <- parent()
filter_call <- self$get_call(sid)
filter_call <- private$reactive_call()
eval_expr_with_msg(filter_call, env)
get(x = dataname, envir = env)
}
Expand Down
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