898 save app state version 3 #710

chlebowa · 2024-03-15T13:13:22Z

Companion to insightsengineering/teal#1011
Replaces uses of update*Input with server-side input creation with renderUI.

Identified encoding elements where logic precludes bookmarking:

tm_g_distribution: dist_param1 and dist_param1: defaults determined dynamically in response to variable, distribution type and "Reset" button press; solved by modifying logic so that the defaults are dead before button is first pressed; added update on button label
tm_a_regression: label_var (outlier label) - default determined each time checkbox is TRUE, which is the case when bookmark is restored; can be partially solved by introducing an always firing version of shiny::restoreInput, which works only once; this solution would disable logic as default would no longer be recomputed
tm_a_pca: "plot specific settings" take reactive dependency on the qenv and cannot be bookmarked.

github-actions · 2024-03-15T15:33:14Z

Code Coverage Summary

Filename                      Stmts    Miss  Cover    Missing
--------------------------  -------  ------  -------  ------------------------------------
R/tm_a_pca.R                    833     833  0.00%    108-1074
R/tm_a_regression.R             779     779  0.00%    153-1037
R/tm_data_table.R               184     184  0.00%    93-330
R/tm_file_viewer.R              172     172  0.00%    44-250
R/tm_front_page.R               132     121  8.33%    70-226
R/tm_g_association.R            336     336  0.00%    135-543
R/tm_g_bivariate.R              674     412  38.87%   308-775, 816, 927, 944, 962, 973-995
R/tm_g_distribution.R          1055    1055  0.00%    122-1315
R/tm_g_response.R               352     352  0.00%    154-579
R/tm_g_scatterplot.R            728     728  0.00%    230-1059
R/tm_g_scatterplotmatrix.R      284     265  6.69%    165-478, 539, 553
R/tm_missing_data.R            1063    1063  0.00%    92-1311
R/tm_outliers.R                 991     991  0.00%    134-1269
R/tm_t_crosstable.R             257     257  0.00%    141-446
R/tm_variable_browser.R         827     822  0.60%    79-1067, 1105-1289
R/utils.R                        99      96  3.03%    82-267
R/zzz.R                           2       2  0.00%    2-3
TOTAL                          8768    8468  3.42%

Diff against main

Filename                      Stmts    Miss  Cover
--------------------------  -------  ------  --------
R/tm_a_pca.R                     +6      +6  +100.00%
R/tm_a_regression.R              +3      +3  +100.00%
R/tm_data_table.R                +5      +5  +100.00%
R/tm_file_viewer.R               +2      +2  +100.00%
R/tm_front_page.R                +3      +3  -0.19%
R/tm_g_association.R             +2      +2  +100.00%
R/tm_g_bivariate.R               +3      +1  +0.12%
R/tm_g_distribution.R           +13     +13  +100.00%
R/tm_g_response.R                +2      +2  +100.00%
R/tm_g_scatterplot.R             +2      +2  +100.00%
R/tm_g_scatterplotmatrix.R       +2      +2  -0.05%
R/tm_missing_data.R              +5      +5  +100.00%
R/tm_outliers.R                  +3      +3  +100.00%
R/tm_t_crosstable.R              +2      +2  +100.00%
R/tm_variable_browser.R          +2      +2  -0.00%
TOTAL                           +55     +53  +0.00%

Results for commit: 9623d52

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

github-actions · 2024-03-15T17:34:56Z

Unit Tests Summary

1 files 6 suites 0s ⏱️
29 tests 29 ✅ 0 💤 0 ❌
67 runs 67 ✅ 0 💤 0 ❌

Results for commit 9623d52.

♻️ This comment has been updated with latest results.

…ring/teal.modules.general into 898_save_app_state3@main

gogonzo · 2024-03-26T10:07:46Z

testing app function

testing shiny app code

options(teal.log_level = "TRACE", teal.show_js_log = TRUE)
library(shiny)
library(teal.widgets)
library(teal.transform)
pkgload::load_all("teal.modules.general")

data <- within(teal_data(), {
  require(nestcolor)
  IRIS <- iris
  MTCARS <- mtcars
  USArrests <- USArrests
  ADSL <- rADSL
  ADTTE <- rADTTE
  ADRS <- rADRS
})
datanames(data) <- c("IRIS", "MTCARS", "USArrests", "ADSL", "ADTTE", "ADRS")
join_keys(data) <- default_cdisc_join_keys[datanames(data)]

shiny_app <- function(module) {
  ui <- function(request) {
    fluidPage(
      bookmarkButton(),
      do.call(module$ui, c(list(id = "teal_module"), module$ui_args))
    )
  }

  server <- function(input, output, session) {
    data_list <-
      args <- c(
        list(id = "teal_module"),
        if ("data" %in% names(formals(module$server))) {
          list(data = reactive(data))
        },
        module$server_args
      )
    do.call(module$server, args)
  }

  shinyApp(ui, server, enableBookmarking = "server")
}

tm_a_pca ❌

app code

shiny_app(
  tm_a_pca(
    "PCA",
    dat = data_extract_spec(
      dataname = "USArrests",
      select = select_spec(
        choices = variable_choices(
          data = "USArrests", c("Murder", "Assault", "UrbanPop", "Rape")
        ),
        selected = c("Murder", "Assault"),
        multiple = TRUE
      ),
      filter = NULL
    ),
    ggplot2_args = ggplot2_args(
      labs = list(subtitle = "Plot generated by PCA Module")
    )
  )
)

tm_a_regression ❌

app code

shiny_app(
  tm_a_regression(
    label = "Regression",
    response = data_extract_spec(
      dataname = "ADSL",
      select = select_spec(
        label = "Select variable:",
        choices = "BMRKR1",
        selected = "BMRKR1",
        multiple = FALSE,
        fixed = TRUE
      )
    ),
    regressor = data_extract_spec(
      dataname = "ADSL",
      select = select_spec(
        label = "Select variables:",
        choices = variable_choices(data[["ADSL"]], c("AGE", "SEX", "RACE")),
        selected = "AGE",
        multiple = TRUE,
        fixed = FALSE
      )
    ),
    ggplot2_args = ggplot2_args(
      labs = list(subtitle = "Plot generated by Regression Module")
    )
  )
)

tm_data_table ✅

app code

shiny_app(teal.modules.general::tm_data_table())

tm_file_viewer ❌

app code

shiny_app(
  tm_file_viewer(
    input_path = list(
      folder = system.file("sample_files", package = "teal.modules.general"),
      png = system.file("sample_files/sample_file.png", package = "teal.modules.general"),
      txt = system.file("sample_files/sample_file.txt", package = "teal.modules.general"),
      url = "https://fda.gov/files/drugs/published/Portable-Document-Format-Specifications.pdf"
    )
  )
)

tm_g_association ✅

app code

shiny_app(
  tm_g_association(
    ref = data_extract_spec(
      dataname = "ADSL",
      select = select_spec(
        label = "Select variable:",
        choices = variable_choices(
          data[["ADSL"]],
          c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
        ),
        selected = "RACE",
        fixed = FALSE
      )
    ),
    vars = data_extract_spec(
      dataname = "ADSL",
      select = select_spec(
        label = "Select variables:",
        choices = variable_choices(
          data[["ADSL"]],
          c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
        ),
        selected = "BMRKR2",
        multiple = TRUE,
        fixed = FALSE
      )
    ),
    ggplot2_args = ggplot2_args(
      labs = list(subtitle = "Plot generated by Association Module")
    )
  )
)

tm_g_bivariate ✅

app code

shiny_app(
  tm_g_bivariate(
    x = data_extract_spec(
      dataname = "ADSL",
      select = select_spec(
        label = "Select variable:",
        choices = variable_choices(data[["ADSL"]]),
        selected = "AGE",
        fixed = FALSE
      )
    ),
    y = data_extract_spec(
      dataname = "ADSL",
      select = select_spec(
        label = "Select variable:",
        choices = variable_choices(data[["ADSL"]]),
        selected = "SEX",
        multiple = FALSE,
        fixed = FALSE
      )
    ),
    row_facet = data_extract_spec(
      dataname = "ADSL",
      select = select_spec(
        label = "Select variable:",
        choices = variable_choices(data[["ADSL"]]),
        selected = "ARM",
        fixed = FALSE
      )
    ),
    col_facet = data_extract_spec(
      dataname = "ADSL",
      select = select_spec(
        label = "Select variable:",
        choices = variable_choices(data[["ADSL"]]),
        selected = "COUNTRY",
        fixed = FALSE
      )
    ),
    ggplot2_args = ggplot2_args(
      labs = list(subtitle = "Plot generated by Bivariate Module")
    )
  )
)

tm_g_distribution ✅

app code

vars1 <- choices_selected(
  variable_choices(data[["ADSL"]], c("ARM", "COUNTRY", "SEX")),
  selected = NULL
)
module <- tm_g_distribution(
  dist_var = data_extract_spec(
    dataname = "ADSL",
    select = select_spec(
      choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
      selected = "BMRKR1",
      multiple = FALSE,
      fixed = FALSE
    )
  ),
  strata_var = data_extract_spec(
    dataname = "ADSL",
    filter = filter_spec(
      vars = vars1,
      multiple = TRUE
    )
  ),
  group_var = data_extract_spec(
    dataname = "ADSL",
    filter = filter_spec(
      vars = vars1,
      multiple = TRUE
    )
  ),
  ggplot2_args = ggplot2_args(
    labs = list(subtitle = "Plot generated by Distribution Module")
  )
)

shiny_app(module)

tm_g_response ✅

app code

module <- tm_g_response(
  label = "Response Plots",
  response = data_extract_spec(
    dataname = "ADSL",
    select = select_spec(
      label = "Select variable:",
      choices = variable_choices(data[["ADSL"]], c("BMRKR2", "COUNTRY")),
      selected = "BMRKR2",
      multiple = FALSE,
      fixed = FALSE
    )
  ),
  x = data_extract_spec(
    dataname = "ADSL",
    select = select_spec(
      label = "Select variable:",
      choices = variable_choices(data[["ADSL"]], c("SEX", "RACE")),
      selected = "RACE",
      multiple = FALSE,
      fixed = FALSE
    )
  ),
  ggplot2_args = ggplot2_args(
    labs = list(subtitle = "Plot generated by Response Module")
  )
)
shiny_app(module)

tm_g_scatterplot ✅

app code

module <- tm_g_scatterplot(
  label = "Scatterplot Choices",
  x = data_extract_spec(
    dataname = "ADSL",
    select = select_spec(
      label = "Select variable:",
      choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2")),
      selected = "AGE",
      multiple = FALSE,
      fixed = FALSE
    )
  ),
  y = data_extract_spec(
    dataname = "ADSL",
    select = select_spec(
      label = "Select variable:",
      choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1", "BMRKR2")),
      selected = "BMRKR1",
      multiple = FALSE,
      fixed = FALSE
    )
  ),
  color_by = data_extract_spec(
    dataname = "ADSL",
    select = select_spec(
      label = "Select variable:",
      choices = variable_choices(
        data[["ADSL"]],
        c("AGE", "BMRKR1", "BMRKR2", "RACE", "REGION1")
      ),
      selected = NULL,
      multiple = FALSE,
      fixed = FALSE
    )
  ),
  size_by = data_extract_spec(
    dataname = "ADSL",
    select = select_spec(
      label = "Select variable:",
      choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
      selected = "AGE",
      multiple = FALSE,
      fixed = FALSE
    )
  ),
  row_facet = data_extract_spec(
    dataname = "ADSL",
    select = select_spec(
      label = "Select variable:",
      choices = variable_choices(data[["ADSL"]], c("BMRKR2", "RACE", "REGION1")),
      selected = NULL,
      multiple = FALSE,
      fixed = FALSE
    )
  ),
  col_facet = data_extract_spec(
    dataname = "ADSL",
    select = select_spec(
      label = "Select variable:",
      choices = variable_choices(data[["ADSL"]], c("BMRKR2", "RACE", "REGION1")),
      selected = NULL,
      multiple = FALSE,
      fixed = FALSE
    )
  ),
  ggplot2_args = ggplot2_args(
    labs = list(subtitle = "Plot generated by Scatterplot Module")
  )
)
shiny_app(module)

tm_g_scatterplotmatrix ✅

app code

shiny_app(
  tm_g_scatterplotmatrix(
    label = "Scatterplot matrix",
    variables = list(
      data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Select variables:",
          choices = variable_choices(data[["ADSL"]]),
          selected = c("AGE", "RACE", "SEX"),
          multiple = TRUE,
          ordered = TRUE,
          fixed = FALSE
        )
      ),
      data_extract_spec(
        dataname = "ADRS",
        filter = filter_spec(
          label = "Select endpoints:",
          vars = c("PARAMCD", "AVISIT"),
          choices = value_choices(data[["ADRS"]], c("PARAMCD", "AVISIT"), c("PARAM", "AVISIT")),
          selected = "INVET - END OF INDUCTION",
          multiple = TRUE
        ),
        select = select_spec(
          label = "Select variables:",
          choices = variable_choices(data[["ADRS"]]),
          selected = c("AGE", "AVAL", "ADY"),
          multiple = TRUE,
          ordered = TRUE,
          fixed = FALSE
        )
      )
    )
  )
)

tm_missing_data ✅

app code

shiny_app(
  tm_missing_data()
)

tm_outliers ✅

app code

fact_vars_adsl <- names(Filter(isTRUE, sapply(data[["ADSL"]], is.factor)))
vars <- choices_selected(variable_choices(data[["ADSL"]], fact_vars_adsl))
shiny_app(
  tm_outliers(
    outlier_var = list(
      data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Select variable:",
          choices = variable_choices(data[["ADSL"]], c("AGE", "BMRKR1")),
          selected = "AGE",
          multiple = FALSE,
          fixed = FALSE
        )
      )
    ),
    categorical_var = list(
      data_extract_spec(
        dataname = "ADSL",
        filter = filter_spec(
          vars = vars,
          choices = value_choices(data[["ADSL"]], vars$selected),
          selected = value_choices(data[["ADSL"]], vars$selected),
          multiple = TRUE
        )
      )
    ),
    ggplot2_args = list(
      ggplot2_args(
        labs = list(subtitle = "Plot generated by Outliers Module")
      )
    )
  )
)

tm_t_crosstable ✅

app code

shiny_app(
  tm_t_crosstable(
    label = "Cross Table",
    x = data_extract_spec(
      dataname = "ADSL",
      select = select_spec(
        label = "Select variable:",
        choices = variable_choices(data[["ADSL"]], subset = function(data) {
          idx <- !vapply(data, inherits, logical(1), c("Date", "POSIXct", "POSIXlt"))
          return(names(data)[idx])
        }),
        selected = "COUNTRY",
        multiple = TRUE,
        ordered = TRUE,
        fixed = FALSE
      )
    ),
    y = data_extract_spec(
      dataname = "ADSL",
      select = select_spec(
        label = "Select variable:",
        choices = variable_choices(data[["ADSL"]], subset = function(data) {
          idx <- vapply(data, is.factor, logical(1))
          return(names(data)[idx])
        }),
        selected = "SEX",
        multiple = FALSE,
        fixed = FALSE
      )
    ),
    basic_table_args = basic_table_args(
      subtitles = "Table generated by Crosstable Module"
    )
  )
)

tm_t_variable_browser ✅

app code

shiny_app(tm_t_variable_browser())

gogonzo

👍

Aleksander Chlebowski added 4 commits March 13, 2024 16:42

use restoreInput in updates: tm_g_distribution

31b7b1b

use restoreInput in updates: tm_a_regression

f2787ef

use restoreInput in updates: tm_missing_data

0bcd71f

use restoreInput in updates: tm_outliers

0ba693a

chlebowa added the core label Mar 15, 2024

chlebowa mentioned this pull request Mar 15, 2024

898 save app state version 3 insightsengineering/teal#1011

Merged

16 tasks

Aleksander Chlebowski added 2 commits March 15, 2024 16:00

Merge branch 'main' into 898_save_app_state3@main

408dbda

all tabsetPanel have id

d4a7836

chlebowa marked this pull request as ready for review March 15, 2024 15:08

[skip style] [skip vbump] Restyle files

1249e72

trigger

5c922f9

chlebowa and others added 17 commits March 18, 2024 10:30

Merge branch 'main' into 898_save_app_state3@main

807ee6b

Merge branch 'main' into 898_save_app_state3@main

6f393e2

simplify logic in tm_g_distribution

efea9d5

modify dist params logic to allow bookmarking

63b8d84

introduce teal_bookmarkable attribute in modules

605a256

break lines

ebf6fb7

clean up

245f0c6

module bookmarkable: tm_t_frontpage

b6da993

module bookmarkable: tm_g_bivariate

f1600ef

module bookmarkable: tm_variable_browser

cde83e2

module bookmarkable: tm_file_viewer

ea841f8

module bookmarkable: tm_g_association

303c787

module bookmarkable: tm_g_response

717595b

module bookmarkable: tm_g_scatterplot

f5c1c2d

module bookmarkable: tm_g_scatterplotmatrix

5383d5c

module bookmarkable: tm_t_crosstable

4af39e3

[skip style] [skip vbump] Restyle files

61cef67

Aleksander Chlebowski added 8 commits March 25, 2024 14:04

fix erroneous bookmarkable flags

b191ed1

Merge branch '898_save_app_state3@main' of github.com:insightsenginee…

e4fbec7

…ring/teal.modules.general into 898_save_app_state3@main

module bookmarkable: tm_outliers

5473cf4

fix linter

76daa5d

remove erroneous bookmarkable flag

41dba68

module bookmarkable: tm_missing_data

3292ba5

fix typo

d866adc

module bookmarkable: tm_a_pca

43011fc

gogonzo added 2 commits March 26, 2024 15:01

fix error

4b17fd1

fixes

9623d52

gogonzo approved these changes Mar 28, 2024

View reviewed changes

chlebowa merged commit 6f19601 into main Mar 28, 2024

chlebowa deleted the 898_save_app_state3@main branch March 28, 2024 16:16

donyunardi mentioned this pull request May 8, 2024

898 save app state version 3 insightsengineering/teal.modules.hermes#372

Draft

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Uh oh!

Uh oh!

898 save app state version 3 #710

898 save app state version 3 #710

Uh oh!

chlebowa commented Mar 15, 2024 •

edited

Loading

Uh oh!

github-actions bot commented Mar 15, 2024 •

edited

Loading

Uh oh!

github-actions bot commented Mar 15, 2024 •

edited

Loading

Uh oh!

gogonzo commented Mar 26, 2024 •

edited

Loading

tm_outliers ✅

tm_t_crosstable ✅

tm_t_variable_browser ✅

Uh oh!

gogonzo left a comment

Uh oh!

Uh oh!

Uh oh!

898 save app state version 3 #710

898 save app state version 3 #710

Uh oh!

Conversation

chlebowa commented Mar 15, 2024 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Uh oh!

github-actions bot commented Mar 15, 2024 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Code Coverage Summary

Diff against main

Uh oh!

github-actions bot commented Mar 15, 2024 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

Unit Tests Summary

Uh oh!

gogonzo commented Mar 26, 2024 • edited Loading Uh oh! There was an error while loading. Please reload this page.

Uh oh!

testing app function

tm_a_pca ❌

tm_a_regression ❌

tm_data_table ✅

tm_file_viewer ❌

tm_g_association ✅

tm_g_bivariate ✅

tm_g_distribution ✅

tm_g_response ✅

tm_g_scatterplot ✅

tm_g_scatterplotmatrix ✅

tm_missing_data ✅

tm_outliers ✅

tm_t_crosstable ✅

tm_t_variable_browser ✅

Uh oh!

gogonzo left a comment

Choose a reason for hiding this comment

Uh oh!

Uh oh!

chlebowa commented Mar 15, 2024 •

edited

Loading

github-actions bot commented Mar 15, 2024 •

edited

Loading

github-actions bot commented Mar 15, 2024 •

edited

Loading

gogonzo commented Mar 26, 2024 •

edited

Loading