tdata to teal_data - tm_g_gh_correlationplot (#249)

**Example app**

```r
data <- teal_data()
data <- within(data, {
  # original ARM value = dose value
  arm_mapping <- list(
    "A: Drug X" = "150mg QD",
    "B: Placebo" = "Placebo",
    "C: Combination" = "Combination"
  )
  color_manual <- c("150mg QD" = "#000000", "Placebo" = "#3498DB", "Combination" = "#E74C3C")
  # assign LOQ flag symbols: circles for "N" and triangles for "Y", squares for "NA"
  shape_manual <- c("N" = 1, "Y" = 2, "NA" = 0)

  set.seed(1)
  ADSL <- goshawk::rADSL
  ADLB <- goshawk::rADLB
  var_labels <- lapply(ADLB, function(x) attributes(x)$label)
  ADLB <- ADLB %>%
    dplyr::mutate(AVISITCD = dplyr::case_when(
      AVISIT == "SCREENING" ~ "SCR",
      AVISIT == "BASELINE" ~ "BL",
      grepl("WEEK", AVISIT) ~
        paste(
          "W",
          trimws(
            substr(
              AVISIT,
              start = 6,
              stop = stringr::str_locate(AVISIT, "DAY") - 1
            )
          )
        ),
      TRUE ~ NA_character_
    )) %>%
    dplyr::mutate(AVISITCDN = dplyr::case_when(
      AVISITCD == "SCR" ~ -2,
      AVISITCD == "BL" ~ 0,
      grepl("W", AVISITCD) ~ as.numeric(gsub("[^0-9]*", "", AVISITCD)),
      TRUE ~ NA_real_
    )) %>%
    # use ARMCD values to order treatment in visualization legend
    dplyr::mutate(TRTORD = ifelse(grepl("C", ARMCD), 1,
      ifelse(grepl("B", ARMCD), 2,
        ifelse(grepl("A", ARMCD), 3, NA)
      )
    )) %>%
    dplyr::mutate(ARM = as.character(arm_mapping[match(ARM, names(arm_mapping))])) %>%
    dplyr::mutate(ARM = factor(ARM) %>%
      reorder(TRTORD)) %>%
    dplyr::mutate(
      ANRHI = dplyr::case_when(
        PARAMCD == "ALT" ~ 60,
        PARAMCD == "CRP" ~ 70,
        PARAMCD == "IGA" ~ 80,
        TRUE ~ NA_real_
      ),
      ANRLO = dplyr::case_when(
        PARAMCD == "ALT" ~ 20,
        PARAMCD == "CRP" ~ 30,
        PARAMCD == "IGA" ~ 40,
        TRUE ~ NA_real_
      )
    ) %>%
    dplyr::rowwise() %>%
    dplyr::group_by(PARAMCD) %>%
    dplyr::mutate(LBSTRESC = ifelse(
      USUBJID %in% sample(USUBJID, 1, replace = TRUE),
      paste("<", round(runif(1, min = 25, max = 30))), LBSTRESC
    )) %>%
    dplyr::mutate(LBSTRESC = ifelse(
      USUBJID %in% sample(USUBJID, 1, replace = TRUE),
      paste(">", round(runif(1, min = 70, max = 75))), LBSTRESC
    )) %>%
    ungroup()
  attr(ADLB[["ARM"]], "label") <- var_labels[["ARM"]]
  attr(ADLB[["ANRHI"]], "label") <- "Analysis Normal Range Upper Limit"
  attr(ADLB[["ANRLO"]], "label") <- "Analysis Normal Range Lower Limit"

  # add LLOQ and ULOQ variables
  ADLB_LOQS <- goshawk:::h_identify_loq_values(ADLB)
  ADLB <- dplyr::left_join(ADLB, ADLB_LOQS, by = "PARAM")
})

datanames <- c("ADSL", "ADLB")
datanames(data) <- datanames

join_keys(data) <- default_cdisc_join_keys[datanames]

app <- teal::init(
  data = data,
  modules = teal::modules(
    teal.goshawk::tm_g_gh_correlationplot(
      label = "Correlation Plot",
      dataname = "ADLB",
      param_var = "PARAMCD",
      xaxis_param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
      yaxis_param = choices_selected(c("ALT", "CRP", "IGA"), "CRP"),
      xaxis_var = choices_selected(c("AVAL", "BASE", "CHG", "PCHG"), "BASE"),
      yaxis_var = choices_selected(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = choices_selected(c("ARM", "ACTARM"), "ARM"),
      color_manual = c(
        "Drug X 100mg" = "#000000",
        "Placebo" = "#3498DB",
        "Combination 100mg" = "#E74C3C"
      ),
      shape_manual = c("N" = 1, "Y" = 2, "NA" = 0),
      plot_height = c(500, 200, 2000),
      facet_ncol = 2,
      visit_facet = TRUE,
      reg_line = FALSE,
      loq_legend = TRUE,
      font_size = c(12, 8, 20),
      dot_size = c(1, 1, 12),
      reg_text_size = c(3, 3, 10),
      hline_arb = c(40, 50),
      hline_arb_label = "arb hori label",
      hline_arb_color = c("red", "blue"),
      hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      hline_vars_colors = c("green", "blue", "purple", "cyan"),
      hline_vars_label = c("ANRHI Label", "ANRLO Label", "ULOQN Label", "LLOQN Label"),
      vline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      vline_vars_colors = c("yellow", "orange", "brown", "gold"),
      vline_vars_labels = c("ANRHI Label", "ANRLO Label", "ULOQN Label", "LLOQN Label"),
      vline_arb = c(50, 70),
      vline_arb_label = "arb vert A",
      vline_arb_color = c("green", "orange")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}
```

R/tm_g_gh_correlationplot.R

@@ -378,7 +378,8 @@ srv_g_correlationplot <- function(id,
                                   vline_vars_labels) {
   with_reporter <- !missing(reporter) && inherits(reporter, "Reporter")
   with_filter <- !missing(filter_panel_api) && inherits(filter_panel_api, "FilterPanelAPI")
-  checkmate::assert_class(data, "tdata")
+  checkmate::assert_class(data, "reactive")
+  checkmate::assert_class(shiny::isolate(data()), "teal_data")
 
   moduleServer(id, function(input, output, session) {
     iv_r <- reactive({
@@ -403,7 +404,7 @@ srv_g_correlationplot <- function(id,
     # filter selected biomarkers
     anl_param <- reactive({
       dataset_var <- dataname
-      ANL <- data[[dataname]]() # nolint
+      ANL <- data()[[dataname]] # nolint
       validate_has_data(ANL, 1)
 
       if (length(input$hline_vars) > 0) {
@@ -492,7 +493,7 @@ srv_g_correlationplot <- function(id,
       )
 
       # analysis
-      private_qenv <- teal.code::new_qenv(tdata2env(data), code = get_code_tdata(data)) %>%
+      private_qenv <- data() %>%
         teal.code::eval_code(
           code = bquote({
             ANL <- .(as.name(dataset_var)) %>% # nolint
@@ -511,7 +512,7 @@ srv_g_correlationplot <- function(id,
       req(constraint_var)
 
       # note that filtered is false thus we cannot use anl_param()$ANL
-      ANL <- data[[dataname]]() # nolint
+      ANL <- data()[[dataname]] # nolint
       validate_has_data(ANL, 1)
 
       validate_has_variable(ANL, param_var)