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tdata to teal_data #246

Merged
merged 7 commits into from
Dec 8, 2023
Merged

tdata to teal_data #246

merged 7 commits into from
Dec 8, 2023

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chlebowa
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@chlebowa chlebowa commented Nov 23, 2023 •
edited by gogonzo
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This is a feature branch, DON'T MERGE and DON'T COMMENT.
PR open to have constant checks.
We will start review this PR as a whole in the sprint 4.

staged.dependencies::dependency_table(
  project = "insightsengineering/teal.goshawk@https://github.com",
  project_type = "repo@host",
  ref = "refactor",
  verbose = 1
) |>
staged.dependencies::install_deps()

@chlebowa chlebowa mentioned this pull request Nov 23, 2023
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github-actions bot commented Nov 23, 2023 •
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Code Coverage Summary

Filename                                 Stmts    Miss  Cover    Missing
-------------------------------------  -------  ------  -------  ---------
R/tm_g_gh_boxplot.R                        351     351  0.00%    172-590
R/tm_g_gh_correlationplot.R                557     557  0.00%    222-885
R/tm_g_gh_density_distribution_plot.R      275     275  0.00%    134-458
R/tm_g_gh_lineplot.R                       564     564  0.00%    160-818
R/tm_g_gh_scatterplot.R                    240     240  0.00%    142-433
R/tm_g_gh_spaghettiplot.R                  292     292  0.00%    189-547
R/toggleable_slider.R                      154     154  0.00%    82-253
R/utils-arbitrary_lines.r                  125     125  0.00%    19-175
R/utils-data_constraints.r                 190     190  0.00%    2-257
R/utils-keep_range_slider_updated.r         23      23  0.00%    8-38
R/utils-maptrt.r                             9       9  0.00%    25-37
R/utils-templ_ui.r                          48      48  0.00%    2-73
R/utils.R                                   39      39  0.00%    12-83
R/zzz.R                                      1       1  0.00%    2
TOTAL                                     2868    2868  0.00%

Diff against main

Filename                                 Stmts    Miss  Cover
-------------------------------------  -------  ------  --------
R/tm_g_gh_boxplot.R                         -2      -2  +100.00%
R/tm_g_gh_correlationplot.R                 +1      +1  +100.00%
R/tm_g_gh_density_distribution_plot.R       -2      -2  +100.00%
R/tm_g_gh_lineplot.R                        +1      +1  +100.00%
R/tm_g_gh_scatterplot.R                     +1      +1  +100.00%
R/tm_g_gh_spaghettiplot.R                   +1      +1  +100.00%
R/utils-arbitrary_lines.r                   +4      +4  +100.00%
R/utils-data_constraints.r                  +4      +4  +100.00%
TOTAL                                       +8      +8  +100.00%

Results for commit: 611d224

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

@chlebowa chlebowa linked an issue Nov 23, 2023 that may be closed by this pull request
Fix modules to use teal_data instead of tdata #242
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averissimo
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🐠 Blocking to prevent merge

Aleksander Chlebowski and others added 4 commits November 23, 2023 13:40
amend NEWS
03bd167
@vedhav
tdata to teal_data - tm_g_gh_correlationplot (#249)
513b54c 
**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)
}
```
@vedhav
tdata to teal_data - Multiple Modules (#248)
3105ef9 
Please test examples from these modules:

### 1. tm_g_gh_boxplot

<details>
  <summary>
  Example app
  </summary>

```r
data <- teal_data()
data <- within(data, {
  library(dplyr)
  library(nestcolor)

  # original ARM value = dose value
  arm_mapping <- list(
    "A: Drug X" = "150mg QD",
    "B: Placebo" = "Placebo",
    "C: Combination" = "Combination"
  )
  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", stringr::str_extract(AVISIT, "(?<=(WEEK ))[0-9]+")),
        TRUE ~ as.character(NA)
      ),
      AVISITCDN = dplyr::case_when(
        AVISITCD == "SCR" ~ -2,
        AVISITCD == "BL" ~ 0,
        grepl("W", AVISITCD) ~ as.numeric(gsub("[^0-9]*", "", AVISITCD)),
        TRUE ~ as.numeric(NA)
      ),
      AVISITCD = factor(AVISITCD) %>% reorder(AVISITCDN),
      TRTORD = dplyr::case_when(
        ARMCD == "ARM C" ~ 1,
        ARMCD == "ARM B" ~ 2,
        ARMCD == "ARM A" ~ 3
      ),
      ARM = as.character(arm_mapping[match(ARM, names(arm_mapping))]),
      ARM = factor(ARM) %>% reorder(TRTORD),
      ACTARM = as.character(arm_mapping[match(ACTARM, names(arm_mapping))]),
      ACTARM = factor(ACTARM) %>% reorder(TRTORD),
      ANRLO = 50,
      ANRHI = 75
    ) %>%
    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[["ACTARM"]], "label") <- var_labels[["ACTARM"]]
  attr(ADLB[["ANRLO"]], "label") <- "Analysis Normal Range Lower Limit"
  attr(ADLB[["ANRHI"]], "label") <- "Analysis Normal Range Upper Limit"

  # add LLOQ and ULOQ variables
  ALB_LOQS <- goshawk:::h_identify_loq_values(ADLB)
  ADLB <- dplyr::left_join(ADLB, ALB_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_boxplot(
      label = "Box Plot",
      dataname = "ADLB",
      param_var = "PARAMCD",
      param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
      yaxis_var = choices_selected(c("AVAL", "BASE", "CHG"), "AVAL"),
      xaxis_var = choices_selected(c("ACTARM", "ARM", "AVISITCD", "STUDYID"), "ARM"),
      facet_var = choices_selected(c("ACTARM", "ARM", "AVISITCD", "SEX"), "AVISITCD"),
      trt_group = choices_selected(c("ARM", "ACTARM"), "ARM"),
      loq_legend = TRUE,
      rotate_xlab = FALSE,
      hline_arb = c(60, 55),
      hline_arb_color = c("grey", "red"),
      hline_arb_label = c("default_hori_A", "default_hori_B"),
      hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      hline_vars_colors = c("pink", "brown", "purple", "black"),
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}
```
</details>

### 2. tm_g_gh_density_distribution_plot

<details>
  <summary>
  Example app
  </summary>

```r
data <- teal_data()
data <- within(data, {
  library(dplyr)
  # original ARM value = dose value
  arm_mapping <- list(
    "A: Drug X" = "150mg QD",
    "B: Placebo" = "Placebo",
    "C: Combination" = "Combination"
  )
  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", stringr::str_extract(AVISIT, "(?<=(WEEK ))[0-9]+")),
        TRUE ~ as.character(NA)
      ),
      AVISITCDN = dplyr::case_when(
        AVISITCD == "SCR" ~ -2,
        AVISITCD == "BL" ~ 0,
        grepl("W", AVISITCD) ~ as.numeric(gsub("[^0-9]*", "", AVISITCD)),
        TRUE ~ as.numeric(NA)
      ),
      AVISITCD = factor(AVISITCD) %>% reorder(AVISITCDN),
      TRTORD = dplyr::case_when(
        ARMCD == "ARM C" ~ 1,
        ARMCD == "ARM B" ~ 2,
        ARMCD == "ARM A" ~ 3
      ),
      ARM = as.character(arm_mapping[match(ARM, names(arm_mapping))]),
      ARM = factor(ARM) %>% reorder(TRTORD),
      ACTARM = as.character(arm_mapping[match(ACTARM, names(arm_mapping))]),
      ACTARM = factor(ACTARM) %>% reorder(TRTORD)
    )

  attr(ADLB[["ARM"]], "label") <- var_labels[["ARM"]]
  attr(ADLB[["ACTARM"]], "label") <- var_labels[["ACTARM"]]
})

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_density_distribution_plot(
      label = "Density Distribution Plot",
      dataname = "ADLB",
      param_var = "PARAMCD",
      param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
      xaxis_var = choices_selected(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = choices_selected(c("ARM", "ACTARM"), "ARM"),
      color_manual = c(
        "150mg QD" = "#000000",
        "Placebo" = "#3498DB",
        "Combination" = "#E74C3C"
      ),
      color_comb = "#39ff14",
      comb_line = TRUE,
      plot_height = c(500, 200, 2000),
      font_size = c(12, 8, 20),
      line_size = c(1, .25, 3),
      hline_arb = c(.02, .05),
      hline_arb_color = c("red", "black"),
      hline_arb_label = c("Horizontal Line A", "Horizontal Line B")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}
```
</details>


### 3. tm_g_gh_lineplot

<details>
  <summary>
  Example app
  </summary>

```r
data <- teal_data()
data <- within(data, {
  library(dplyr)
  library(stringr)
  library(nestcolor)

  # original ARM value = dose value
  arm_mapping <- list(
    "A: Drug X" = "150mg QD",
    "B: Placebo" = "Placebo",
    "C: Combination" = "Combination"
  )

  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", stringr::str_extract(AVISIT, "(?<=(WEEK ))[0-9]+")),
        TRUE ~ as.character(NA)
      ),
      AVISITCDN = dplyr::case_when(
        AVISITCD == "SCR" ~ -2,
        AVISITCD == "BL" ~ 0,
        grepl("W", AVISITCD) ~ as.numeric(gsub("[^0-9]*", "", AVISITCD)),
        TRUE ~ as.numeric(NA)
      ),
      AVISITCD = factor(AVISITCD) %>% reorder(AVISITCDN),
      TRTORD = dplyr::case_when(
        ARMCD == "ARM C" ~ 1,
        ARMCD == "ARM B" ~ 2,
        ARMCD == "ARM A" ~ 3
      ),
      ARM = as.character(arm_mapping[match(ARM, names(arm_mapping))]),
      ARM = factor(ARM) %>% reorder(TRTORD),
      ACTARM = as.character(arm_mapping[match(ACTARM, names(arm_mapping))]),
      ACTARM = factor(ACTARM) %>% reorder(TRTORD)
    )
  attr(ADLB[["ARM"]], "label") <- var_labels[["ARM"]]
  attr(ADLB[["ACTARM"]], "label") <- var_labels[["ACTARM"]]
})

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_lineplot(
      label = "Line Plot",
      dataname = "ADLB",
      param_var = "PARAMCD",
      param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
      shape_choices = c("SEX", "RACE"),
      xaxis_var = choices_selected("AVISITCD", "AVISITCD"),
      yaxis_var = choices_selected(c("AVAL", "BASE", "CHG", "PCHG"), "AVAL"),
      trt_group = choices_selected(c("ARM", "ACTARM"), "ARM"),
      hline_arb = c(20.5, 19.5),
      hline_arb_color = c("red", "green"),
      hline_arb_label = c("A", "B")
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}
```
</details>


### 4. tm_g_gh_scatterplot

<details>
  <summary>
  Example app
  </summary>

```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"
  )

  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", stringr::str_extract(AVISIT, "(?<=(WEEK ))[0-9]+")),
        TRUE ~ as.character(NA)
      ),
      AVISITCDN = dplyr::case_when(
        AVISITCD == "SCR" ~ -2,
        AVISITCD == "BL" ~ 0,
        grepl("W", AVISITCD) ~ as.numeric(gsub("[^0-9]*", "", AVISITCD)),
        TRUE ~ as.numeric(NA)
      ),
      AVISITCD = factor(AVISITCD) %>% stats::reorder(AVISITCDN),
      TRTORD = dplyr::case_when(
        ARMCD == "ARM C" ~ 1,
        ARMCD == "ARM B" ~ 2,
        ARMCD == "ARM A" ~ 3
      ),
      ARM = as.character(arm_mapping[match(ARM, names(arm_mapping))]),
      ARM = factor(ARM) %>% stats::reorder(TRTORD),
      ACTARM = as.character(arm_mapping[match(ACTARM, names(arm_mapping))]),
      ACTARM = factor(ACTARM) %>% stats::reorder(TRTORD)
    )
  attr(ADLB[["ARM"]], "label") <- var_labels[["ARM"]]
  attr(ADLB[["ACTARM"]], "label") <- var_labels[["ACTARM"]]
})

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_scatterplot(
      label = "Scatter Plot",
      dataname = "ADLB",
      param_var = "PARAMCD",
      param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
      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(
        "150mg QD" = "#000000",
        "Placebo" = "#3498DB",
        "Combination" = "#E74C3C"
      ),
      shape_manual = c("N" = 1, "Y" = 2, "NA" = 0),
      plot_height = c(500, 200, 2000),
      facet_ncol = 2,
      trt_facet = FALSE,
      reg_line = FALSE,
      font_size = c(12, 8, 20),
      dot_size = c(1, 1, 12),
      reg_text_size = c(3, 3, 10)
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}
```
</details>


### 5. tm_g_gh_spaghettiplot

<details>
  <summary>
  Example app
  </summary>

```r
data <- teal_data()
data <- within(data, {
  library(dplyr)

  # original ARM value = dose value
  arm_mapping <- list(
    "A: Drug X" = "150mg QD",
    "B: Placebo" = "Placebo",
    "C: Combination" = "Combination"
  )
  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", stringr::str_extract(AVISIT, "(?<=(WEEK ))[0-9]+")),
        TRUE ~ as.character(NA)
      ),
      AVISITCDN = dplyr::case_when(
        AVISITCD == "SCR" ~ -2,
        AVISITCD == "BL" ~ 0,
        grepl("W", AVISITCD) ~ as.numeric(gsub("[^0-9]*", "", AVISITCD)),
        TRUE ~ as.numeric(NA)
      ),
      AVISITCD = factor(AVISITCD) %>% reorder(AVISITCDN),
      TRTORD = dplyr::case_when(
        ARMCD == "ARM C" ~ 1,
        ARMCD == "ARM B" ~ 2,
        ARMCD == "ARM A" ~ 3
      ),
      ARM = as.character(arm_mapping[match(ARM, names(arm_mapping))]),
      ARM = factor(ARM) %>% reorder(TRTORD),
      ACTARM = as.character(arm_mapping[match(ACTARM, names(arm_mapping))]),
      ACTARM = factor(ACTARM) %>% reorder(TRTORD),
      ANRLO = 30,
      ANRHI = 75
    ) %>%
    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[["ACTARM"]], "label") <- var_labels[["ACTARM"]]
  attr(ADLB[["ANRLO"]], "label") <- "Analysis Normal Range Lower Limit"
  attr(ADLB[["ANRHI"]], "label") <- "Analysis Normal Range Upper Limit"

  # add LLOQ and ULOQ variables
  ALB_LOQS <- goshawk:::h_identify_loq_values(ADLB)
  ADLB <- dplyr::left_join(ADLB, ALB_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_spaghettiplot(
      label = "Spaghetti Plot",
      dataname = "ADLB",
      param_var = "PARAMCD",
      param = choices_selected(c("ALT", "CRP", "IGA"), "ALT"),
      idvar = "USUBJID",
      xaxis_var = choices_selected(c("Analysis Visit Code" = "AVISITCD"), "AVISITCD"),
      yaxis_var = choices_selected(c("AVAL", "CHG", "PCHG"), "AVAL"),
      filter_var = choices_selected(
        c("None" = "NONE", "Screening" = "BASE2", "Baseline" = "BASE"),
        "NONE"
      ),
      trt_group = choices_selected(c("ARM", "ACTARM"), "ARM"),
      color_comb = "#39ff14",
      man_color = c(
        "Combination" = "#000000",
        "Placebo" = "#fce300",
        "150mg QD" = "#5a2f5f"
      ),
      hline_arb = c(60, 50),
      hline_arb_color = c("grey", "red"),
      hline_arb_label = c("default A", "default B"),
      hline_vars = c("ANRHI", "ANRLO", "ULOQN", "LLOQN"),
      hline_vars_colors = c("pink", "brown", "purple", "black"),
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}
```
</details>
@vedhav
fix: ci fixes - lints and docs
1dd6c0f
@vedhav vedhav added the blocked label Nov 24, 2023
@chlebowa chlebowa removed the blocked label Nov 24, 2023
gogonzo
gogonzo approved these changes Dec 8, 2023
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👍

@gogonzo gogonzo merged commit fbdb169 into main Dec 8, 2023
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@gogonzo gogonzo deleted the refactor branch December 8, 2023 13:43
@donyunardi donyunardi mentioned this pull request Jul 26, 2024
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@gogonzo gogonzo gogonzo approved these changes

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Fix modules to use teal_data instead of tdata
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@chlebowa @averissimo @gogonzo @vedhav @kartikeyakirar