## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
library(shinyCohortBuilder)

## -----------------------------------------------------------------------------
library(cohortBuilder)
iris_source <- set_source(tblist(iris = iris))
species_filter <- filter(
  type = "discrete", 
  id = "species",
  dataset = "iris",
  variable = "Species",
  value = "setosa"
)

## -----------------------------------------------------------------------------
evaled_filter <- species_filter(iris_source)
class(evaled_filter)

## -----------------------------------------------------------------------------
str(evaled_filter, give.attr = FALSE)

## ----eval = FALSE-------------------------------------------------------------
# .gui_filter.discrete <- function(filter, ...) {
#   list(
#     input = function(input_id, cohort) {
#       shiny::tagList(
#         .cb_input(
#           do.call(
#             shiny::checkboxGroupInput,
#             discrete_input_params(filter, input_id, cohort, ...)
#           ),
#           filter$input_param
#         ),
#         .cb_input(
#           keep_na_input(input_id, filter, cohort),
#           "keep_na"
#         )
#       )
#     },
#     # other objects
#   )
# }

## ----eval = FALSE-------------------------------------------------------------
# do.call(
#   shiny::checkboxGroupInput,
#   discrete_input_params(filter, input_id, cohort, ...)
# )

## ----eval = FALSE-------------------------------------------------------------
# if (!cohort$get_cache(step_id, filter_id, state = "pre")$n_data) {
#   return(
#     list(inputId = input_id, choices = character(0), selected = character(0), label = NULL)
#   )
# }

## ----eval = FALSE-------------------------------------------------------------
# step_id <- filter$step_id
# filter_id <- filter$id

## ----eval = FALSE-------------------------------------------------------------
# filter_params <- filter$get_params()

## ----eval = FALSE-------------------------------------------------------------
# filter_params[[filter$input_param]]

## ----eval = FALSE-------------------------------------------------------------
# names(
#   cohort$get_cache(step_id, filter_id, state = "pre")$choices
# )

## ----eval = FALSE-------------------------------------------------------------
# names(
#   cohort$get_cache(step_id, filter_id, state = "pre")$choices
# )

## ----eval = FALSE-------------------------------------------------------------
# !is.null(filter_params$value_mapping)

## ----eval = FALSE-------------------------------------------------------------
# cohort$get_source()$attributes$value_mappings[[filter_params$value_mapping]]

## ----eval = FALSE-------------------------------------------------------------
# .pre_post_stats_text(
#   name = <choices labels names vector>,
#   current = <current step statistics vector>,
#   previous = <previous step statistics vector>,
#   stats = <"pre, post", both or NULL> # it's recommended to use `stats = cohort$attributes$stats` to inherit the option from Cohort configuration
# )

## -----------------------------------------------------------------------------
.pre_post_stats_text(
  name = c("A", "B"),
  current = 1:2,
  previous = 3:4,
  stats = c("pre", "post")
)

## ----eval = FALSE-------------------------------------------------------------
# .gui_filter.discrete <- function(filter, ...) {
#   list(
#     feedback = function(input_id, cohort, empty = FALSE) {
#       list(
#         plot_id = shiny::NS(input_id, "feedback_plot") ,
#         output_fun = ggiraph::girafeOutput,
#         render_fun = if (!is.null(empty)) {
#           ggiraph::renderGirafe({
#             if(empty) { # when no data in parent step
#               return(
#                 ggiraph::girafe(
#                   ggobj      = ggplot2::ggplot(),
#                   width_svg  = 10,
#                   height_svg = 0.1
#                 )
#               )
#             }
#             step_id <- filter$step_id
#             filter_id <- filter$id
# 
#             filter_cache <- cohort$get_cache(step_id, filter_id, state = "pre")
#             filter_value <- extract_selected_value(filter$get_params()$value, filter_cache$choices, FALSE)
#             plot_data <- filter_cache$choices[filter_value]
#             n_missing <- filter_cache$n_missing
#             if (identical(filter$get_params()$keep_na, FALSE)) {
#               n_missing <- 0
#             }
# 
#             plot_feedback_bar(plot_data, n_missing)
#           })
#         }
#       )
#     },
#     # other methods
#   )
# }

## ----eval = FALSE-------------------------------------------------------------
# step_id <- filter$step_id
# filter_id <- filter$id

## ----eval = FALSE-------------------------------------------------------------
# .gui_filter.discrete <- function(filter, ...) {
#   list(
#     server = function(input_id, input, output, session, cohort) {
#       shiny::observeEvent(input[[shiny::NS(input_id, "feedback_plot_selected")]], {
#         value <- input[[shiny::NS(input_id, "feedback_plot_selected")]]
# 
#         if (!is.na(value)) {
#           .trigger_action(session, "update_filter", params = list(
#             step_id = filter$step_id, filter_id = filter$id,
#             input_name = filter$input_param, input_value = value,
#             run_flow = FALSE
#           ))
#         }
#       }, ignoreInit = TRUE) %>% .save_observer(input_id, session)
#     },
#     # other methods
#   )
# }

## ----eval = FALSE-------------------------------------------------------------
# .gui_filter.discrete <- function(filter, ...) {
#   list(
#     update = function(session, input_id, cohort, reset = FALSE, ...) {
#       update_params <- discrete_input_params(filter, input_id, cohort, reset = reset, update = TRUE, ...)
#       do.call(
#         shiny::updateCheckboxGroupInput,
#         append(
#           list(session = session),
#           update_params
#         )
#       )
#       .update_keep_na_input(session, input_id, filter, cohort)
#     },
#     # other methods
#   )
# }

## ----eval = FALSE-------------------------------------------------------------
# names(
#   cohort$get_cache(step_id, filter_id, state = "pre")$choices
# )

## ----eval = FALSE-------------------------------------------------------------
# label = if (update) character(0) else NULL

