fix as cran (#177)

DESCRIPTION

@@ -46,8 +46,6 @@ Suggests:
     scda.2021 (>= 0.1.3),
     teal.data (>= 0.1.1),
     testthat (>= 2.0)
-VignetteBuilder:
-    knitr
 Remotes:
     insightsengineering/osprey@*release,
     insightsengineering/scda.2021@*release,

R/tm_g_ae_oview.R

@@ -16,8 +16,9 @@
 #' library(scda)
 #' library(nestcolor)
 #'
-#' ADSL <- synthetic_cdisc_data("latest")$adsl
-#' ADAE <- synthetic_cdisc_data("latest")$adae
+#' latest_data <- synthetic_cdisc_data("latest")
+#' ADSL <- latest_data$adsl
+#' ADAE <- latest_data$adae
 #'
 #' # Add additional dummy causality flags.
 #' add_event_flags <- function(dat) {

R/tm_g_heat_bygrade.R

@@ -34,10 +34,11 @@
 #' library(scda)
 #' library(dplyr)
 #' library(nestcolor)
-#' ADSL <- synthetic_cdisc_data("latest")$adsl %>% slice(1:30)
-#' ADEX <- synthetic_cdisc_data("latest")$adex %>% filter(USUBJID %in% ADSL$USUBJID)
-#' ADAE <- synthetic_cdisc_data("latest")$adae %>% filter(USUBJID %in% ADSL$USUBJID)
-#' ADCM <- synthetic_cdisc_data("latest")$adcm %>% filter(USUBJID %in% ADSL$USUBJID)
+#' latest_data <- synthetic_cdisc_data("latest")
+#' ADSL <- latest_data$adsl %>% slice(1:30)
+#' ADEX <- latest_data$adex %>% filter(USUBJID %in% ADSL$USUBJID)
+#' ADAE <- latest_data$adae %>% filter(USUBJID %in% ADSL$USUBJID)
+#' ADCM <- latest_data$adcm %>% filter(USUBJID %in% ADSL$USUBJID)
 #'
 #' # This preprocess is only to force legacy standard on ADCM
 #' ADCM <- ADCM %>%
@@ -76,10 +77,11 @@
 #'     cdisc_dataset("ADAE", ADAE),
 #'     cdisc_dataset("ADCM", ADCM, keys = c("STUDYID", "USUBJID", "ASTDTM", "CMSEQ", "CMDECOD")),
 #'     code = "
-#'     ADSL <- synthetic_cdisc_data(\"latest\")$adsl %>% slice(1:30)
-#'     ADEX <- synthetic_cdisc_data(\"latest\")$adex %>% filter(USUBJID %in% ADSL$USUBJID)
-#'     ADAE <- synthetic_cdisc_data(\"latest\")$adae %>% filter(USUBJID %in% ADSL$USUBJID)
-#'     ADCM <- synthetic_cdisc_data(\"latest\")$adcm %>% filter(USUBJID %in% ADSL$USUBJID)
+#'     latest_data <- synthetic_cdisc_data('latest')
+#'     ADSL <- latest_data$adsl %>% slice(1:30)
+#'     ADEX <- latest_data$adex %>% filter(USUBJID %in% ADSL$USUBJID)
+#'     ADAE <- latest_data$adae %>% filter(USUBJID %in% ADSL$USUBJID)
+#'     ADCM <- latest_data$adcm %>% filter(USUBJID %in% ADSL$USUBJID)
 #'     ADCM <- ADCM %>% select(-starts_with(\"ATC\")) %>% unique()
 #'     ADEX  <- ADEX %>%
 #'       filter(PARCAT1 == 'INDIVIDUAL') %>%
@@ -324,7 +326,7 @@ srv_g_heatmap_bygrade <- function(id,
     observeEvent(input$plot_cm, {
       ADCM <- datasets$get_data(cm_dataname, filtered = TRUE) # nolint
       ADCM_label <- formatters::var_labels(datasets$get_data(cm_dataname, filtered = FALSE), fill = FALSE) # nolint
-      formatters::var_labels(ADCM) <- ADCM_label
+      formatters::var_labels(ADCM) <- ADCM_label # nolint
       choices <- levels(ADCM[[input$conmed_var]])
 
       updateSelectInput(
@@ -347,11 +349,11 @@ srv_g_heatmap_bygrade <- function(id,
       ADAE <- datasets$get_data(ae_dataname, filtered = TRUE) # nolint
 
       # assign labels back to the data
-      formatters::var_labels(ADSL) <-
+      formatters::var_labels(ADSL) <- # nolint
         formatters::var_labels(datasets$get_data(sl_dataname, filtered = FALSE), fill = FALSE)
-      formatters::var_labels(ADEX) <-
+      formatters::var_labels(ADEX) <- # nolint
         formatters::var_labels(datasets$get_data(ex_dataname, filtered = FALSE), fill = FALSE)
-      formatters::var_labels(ADAE) <-
+      formatters::var_labels(ADAE) <- # nolint
         formatters::var_labels(datasets$get_data(ae_dataname, filtered = FALSE), fill = FALSE)
 
       validate(need(nrow(ADSL) > 0, "Please select at least one subject"))
@@ -379,7 +381,7 @@ srv_g_heatmap_bygrade <- function(id,
       if (input$plot_cm) {
         ADCM <- datasets$get_data(cm_dataname, filtered = TRUE) # nolint
         ADCM_label <- formatters::var_labels(datasets$get_data(cm_dataname, filtered = FALSE), fill = FALSE) # nolint
-        formatters::var_labels(ADCM) <- ADCM_label
+        formatters::var_labels(ADCM) <- ADCM_label # nolint
         validate(
           need(
             input$conmed_var %in% names(ADCM),

R/tm_g_patient_profile.R

@@ -84,13 +84,15 @@
 #' library(scda)
 #' library(nestcolor)
 #'
-#' ADSL <- synthetic_cdisc_data("latest")$adsl
-#' ADAE <- synthetic_cdisc_data("latest")$adae %>%
+#' latest_data <- synthetic_cdisc_data("latest")
+#'
+#' ADSL <- latest_data$adsl
+#' ADAE <- latest_data$adae %>%
 #'   mutate(
 #'     ASTDT = as.Date(ASTDTM),
 #'     AENDT = as.Date(AENDTM)
 #'   )
-#' ADCM <- synthetic_cdisc_data("latest")$adcm %>%
+#' ADCM <- latest_data$adcm %>%
 #'   mutate(
 #'     ASTDT = as.Date(ASTDTM),
 #'     AENDT = as.Date(AENDTM)
@@ -101,14 +103,14 @@
 #'   select(-starts_with("ATC")) %>%
 #'   unique()
 #'
-#' ADRS <- synthetic_cdisc_data("latest")$adrs %>%
+#' ADRS <- latest_data$adrs %>%
 #'   mutate(ADT = as.Date(ADTM))
-#' ADEX <- synthetic_cdisc_data("latest")$adex %>%
+#' ADEX <- latest_data$adex %>%
 #'   mutate(
 #'     ASTDT = as.Date(ASTDTM),
 #'     AENDT = as.Date(AENDTM)
 #'   )
-#' ADLB <- synthetic_cdisc_data("latest")$adlb %>%
+#' ADLB <- latest_data$adlb %>%
 #'   mutate(
 #'     ADT = as.Date(ADTM),
 #'     LBSTRESN = as.numeric(LBSTRESC)
@@ -145,7 +147,7 @@
 #'               mutate(ASTDT = as.Date(ASTDTM),
 #'                      AENDT = as.Date(AENDTM))"
 #'     ),
-#'     check = TRUE
+#'     check = FALSE # set FALSE here to keep run time of example short, should be set to TRUE
 #'   ),
 #'   modules = modules(
 #'     tm_g_patient_profile(
@@ -564,7 +566,7 @@ srv_g_patient_profile <- function(id,
           ADAE <- NULL # nolint
         } else {
           ADAE <- datasets$get_data(ae_dataname, filtered = TRUE) # nolint
-          formatters::var_labels(ADAE) <- formatters::var_labels(
+          formatters::var_labels(ADAE) <- formatters::var_labels( # nolint
             datasets$get_data(ae_dataname, filtered = FALSE),
             fill = FALSE
           )
@@ -654,7 +656,7 @@ srv_g_patient_profile <- function(id,
         expression = bquote({
           ADSL <- ADSL %>% # nolint
             group_by(.data$USUBJID)
-          ADSL$max_date <- pmax(
+          ADSL$max_date <- pmax( # nolint
             as.Date(ADSL$LSTALVDT),
             as.Date(ADSL$DTHDT),
             na.rm = TRUE
@@ -745,7 +747,7 @@ srv_g_patient_profile <- function(id,
                     as.character(eval(parse(text = .(sl_start_date), keep.source = FALSE))), 1, 10
                   )))) %>%
                 select(c(.(adae_vars), ASTDY, AENDY))
-              formatters::var_labels(ADAE)[.(ae_line_col_var)] <-
+              formatters::var_labels(ADAE)[.(ae_line_col_var)] <- # nolint
                 formatters::var_labels(ADAE, fill = FALSE)[.(ae_line_col_var)]
             })
           )

README.md

@@ -1,6 +1,6 @@
 # teal.osprey
 
-The teal.osprey package provides community contributed `teal` modules of the analysis functions from the [osprey](https://insightsengineering.github.io/osprey) R package.
+The teal.osprey package provides community contributed `teal` modules of the analysis functions from the [osprey](https://insightsengineering.github.io/osprey/) R package.
 This enables `teal` app developers to easily create applications making use of the `osprey` analysis functions.
 
 ## Installation
@@ -15,7 +15,7 @@ remotes::install_github("insightsengineering/teal.osprey@*release")
 
 A stable release of all `NEST` packages from June 2022 is also available [here](https://github.com/insightsengineering/depository#readme).
 
-In order to run many of the examples you will also need to install the [`scda`](https://insightsengineering.github.io/scda) package.
+In order to run many of the examples you will also need to install the [`scda`](https://insightsengineering.github.io/scda/) package.
 
 ## Stargazers and Forkers