fixing shinytest2 fail for tm_missing_data

[kartikeyakirar]

A test in tm_missing_data is failing because a slider's default value gives an error. It passed in PR 727 with a value of 2L, but here it was showing 1L. I fixed it in PR 733 with app_driver$get_active_module_input("iris-combination_cutoff"), but it's causing an error in another PR again.

To fix I have set.seed in teal_data()

[github-actions]

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              678     416  38.64%   303-775, 816, 927, 944, 962, 973-995
R/tm_g_distribution.R          1056    1056  0.00%    122-1317
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            1075    1075  0.00%    92-1323
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         829     824  0.60%    79-1069, 1107-1291
R/utils.R                        99      96  3.03%    82-267
R/zzz.R                           2       2  0.00%    2-3
TOTAL                          8787    8487  3.41%

Diff against main

Filename      Stmts    Miss  Cover
----------  -------  ------  --------
TOTAL             0       0  +100.00%

Results for commit: 4ccfb94

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

[github-actions]

Unit Tests Summary

  1 files   20 suites   10m 6s ⏱️
103 tests 103 ✅ 0 💤 0 ❌
418 runs  418 ✅ 0 💤 0 ❌

Results for commit 4ccfb94.

♻️ This comment has been updated with latest results.

[github-actions]

Unit Test Performance Difference

Test Suite	$Status$	Time on main	$±Time$	$±Tests$	$±Skipped$	$±Failures$	$±Errors$
shinytest2-tm_g_bivariate	💚	$45.51$	$-1.51$	$0$	$0$	$0$	$0$
shinytest2-tm_g_scatterplot	💚	$76.20$	$-1.90$	$0$	$0$	$0$	$0$
shinytest2-tm_g_scatterplotmatrix	💚	$24.45$	$-1.64$	$0$	$0$	$0$	$0$
shinytest2-tm_outliers	💚	$87.26$	$-1.98$	$0$	$0$	$0$	$0$

Additional test case details

Test Suite	$Status$	Time on main	$±Time$	Test Case
shinytest2-tm_g_scatterplot	💚	$44.23$	$-1.19$	e2e_tm_g_scatterplot_encoding_inputs_produce_output_without_validation_errors

Results for commit fee5414

♻️ This comment has been updated with latest results.

[m7pr]

Yeah, so without set.seed(123) I get different data each time, hence different cut.off value

as this combination cutoff is dependent on the number of NAs in the data

   combination_cutoff_q <- reactive({
      req(common_code_q())
      teal.code::eval_code(
        common_code_q(),
        quote(
          combination_cutoff <- ANL %>%
            dplyr::mutate_all(is.na) %>%
            dplyr::group_by_all() %>%
            dplyr::tally() %>%
            dplyr::ungroup()
        )
      )
    })

    output$cutoff <- renderUI({
      x <- combination_cutoff_q()[["combination_cutoff"]]$n

      # select 10-th from the top
      n <- length(x)
      idx <- max(1, n - 10)
      prev_value <- isolate(input$combination_cutoff)
      value <- `if`(
        is.null(prev_value) || prev_value > max(x) || prev_value < min(x),
        sort(x, partial = idx)[idx], prev_value
      )

      teal.widgets::optionalSliderInputValMinMax(
        ns("combination_cutoff"),
        "Combination cut-off",
        c(value, range(x))
      )
    })

[m7pr]

And with set.seed before data creation, the data input is the same, hence the calculations for the output are the same