# remember that this test works on the installed version of the code, not devtools::load_all()!


# test_that("{shinytest2} recording: fix_ladder-checkbox", {
#   # Don't run these tests on the CRAN build servers
#   skip_on_cran()
#   skip_on_ci()
#   config <- load_config()
#   fsa_list <- lapply(trace::cell_line_fsa_list[1:2], function(x) x$clone())


#   find_ladders(fsa_list,
#     config,
#     ladder_sizes = c(35, 50, 75, 100, 139, 150, 160, 200, 250, 300, 340, 350, 400, 450, 490, 500),
#     max_combinations = 2500000,
#     ladder_selection_window = 8,
#     show_progress_bar = FALSE
#   )

#   example_list <- list(
#     "20230413_A08.fsa" = data.frame(
#       size = c(35, 50, 75, 100, 139, 150, 160, 200, 250, 300, 340, 350, 400, 450, 490, 500),
#       scan = c(1544, 1621, 1850, 1912, 2143, 2201, 2261, 2506, 2805, 3135, 3380, 3442, 3760, 4050, 4284, 4332)
#     )
#   )

#   suppressMessages(
#     suppressWarnings(
#       fix_ladders_manual(
#         fsa_list,
#         example_list
#       )
#     )
#   )


#   # to generate the values below I ran a test like below and copied the values
#   # shinytest2::record_test(fix_ladders_interactive(fsa_list))


#   suppressMessages(
#     shiny_app <- fix_ladders_interactive(fsa_list)
#   )

  
#   app <- shinytest2::AppDriver$new(shiny_app, width = 1235, height = 826)
#   # Update output value

#   app$set_inputs(`plotly_afterplot-A` = "\"plot_module-plot\"", allow_no_input_binding_ = TRUE, priority_ = "event")
#   app$set_inputs(`plotly_relayout-A` = "{\"width\":782.2625122070312,\"height\":400}", allow_no_input_binding_ = TRUE, priority_ = "event")
#   # Update output value
#   app$set_inputs(`plotly_hover-A` = "[{\"curveNumber\":0,\"pointNumber\":4946,\"x\":4946,\"y\":22}]", allow_no_input_binding_ = TRUE, priority_ = "event")
#   app$set_inputs(`plotly_hover-A` = character(0), allow_no_input_binding_ = TRUE, priority_ = "event")
#   app$set_inputs(`sample_selection-unique_id_selection` = "20230413_A08.fsa", wait_ = FALSE)


#   rsq_table_html <- app$get_values()$output$`rsq_table-rsq_table`

#   # Extract numbers with decimal points using regular expressions
#   matches <- gregexpr("\\b\\d+(\\.\\d+)?\\b(?= </td> </tr>\\n)", rsq_table_html, perl = TRUE)

#   # Extract matched numbers
#   numbers <- regmatches(rsq_table_html, matches)[[1]]
#   numbers <- round(as.numeric(numbers), 4)


#   # I got these numbers by changing to second sample and moving 75 back to the right place, then round as above and remove the 1.0000
#   expect_identical(numbers, c(0.9816, 0.9011, 0.9621, 0.9996, 0.9986, 1.0000, 1.0000, 0.9992, 0.9996, 1.0000, 1.0000, 0.9993, 1.0000, 0.9991))




#   # Update output value
#   app$set_inputs(`plotly_hover-A` = "[{\"curveNumber\":0,\"pointNumber\":2143,\"x\":2143,\"y\":1877}]", allow_no_input_binding_ = TRUE, priority_ = "event")
#   app$set_inputs(`plotly_hover-A` = character(0), allow_no_input_binding_ = TRUE, priority_ = "event")
#   app$set_inputs(`plotly_hover-A` = "[{\"curveNumber\":0,\"pointNumber\":1912,\"x\":1912,\"y\":1700}]", allow_no_input_binding_ = TRUE, priority_ = "event")
#   app$set_inputs(`plotly_hover-A` = character(0), allow_no_input_binding_ = TRUE, priority_ = "event")
#   app$set_inputs(`plotly_afterplot-A` = "\"plot_module-plot\"", allow_no_input_binding_ = TRUE, priority_ = "event")
#   app$set_inputs(`plotly_relayout-A` = "{\"shapes[2].x0\":1774.6904494382022,\"shapes[2].x1\":1774.6904494382022,\"shapes[2].y0\":0.050000000000000044,\"shapes[2].y1\":0.44999999999999996}", allow_no_input_binding_ = TRUE, priority_ = "event")

#   rsq_table_html <- app$get_values()$output$`rsq_table-rsq_table`

#   # Extract numbers with decimal points using regular expressions
#   matches <- gregexpr("\\b\\d+(\\.\\d+)?\\b(?= </td> </tr>\\n)", rsq_table_html, perl = TRUE)

#   # Extract matched numbers
#   numbers <- regmatches(rsq_table_html, matches)[[1]]
#   numbers <- round(as.numeric(numbers), 4)


#   # I got these numbers by changing to second sample and moving 75 back to the right place, then round as above and remove the 1.0000
#   expect_identical(numbers, c(0.9986, 0.9999, 0.9999, 0.9996, 0.9986, 1.0000, 1.0000, 0.9992, 0.9996, 1.0000, 1.0000, 0.9993, 1.0000, 0.9991))
# })