phase out of scda and intro of {pharmaverseadam}

DESCRIPTION

@@ -16,7 +16,7 @@ Authors@R: c(
     person("F. Hoffmann-La Roche AG", role = c("cph", "fnd"))
   )
 Description: Tests of sample templates from TLG Catalog using data from
-    the scda package.
+    `random.cdisc.data` package.
 License: Apache License 2.0 | file LICENSE
 URL: https://github.com/insightsengineering/scda.test/
 BugReports: https://github.com/insightsengineering/scda.test/issues
@@ -27,8 +27,7 @@ Depends:
     rtables (>= 0.6.5.9004),
     tern (>= 0.9.2.9001)
 Imports:
-    scda (>= 0.1.6.9012),
-    scda.2022 (>= 0.1.5.9002)
+    random.cdisc.data (>= 0.3.14.9002)
 Suggests:
     broom,
     checkmate,

NAMESPACE

@@ -1,8 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
 import(formatters)
+import(random.cdisc.data)
 import(rtables)
-import(scda)
-import(scda.2022)
 import(tern)
 importFrom(rlistings,as_listing)

R/scda.test.R

@@ -10,6 +10,6 @@
 
 
 # Fix R CMD check notes
-#' @import formatters rtables tern scda scda.2022
+#' @import formatters rtables tern random.cdisc.data
 #' @importFrom rlistings as_listing
 NULL

README.md

@@ -1,16 +1,15 @@
 # scda.test
 
-Internal repository to store tests that utilize datasets from the `scda` package. Repository tests TLG sample templates to verify functionality and correct output. Template tests were migrated here from the `tern` package in February 2023.
+Internal repository to store tests that utilize datasets from the `random.cdisc.data` package. Repository tests TLG sample templates to verify functionality and correct output. Template tests were migrated here from the `tern` package in February 2023.
 
 ## Installation
 
 ### Installing Package Dependencies
 
-The `scda.test` package has several dependencies required to run the tests within this package. Before installing the `scda.test` repository, please ensure you have the latest versions of the `tern`, `scda`, and `scda.2022` packages installed. Installation instructions are provided for each at these links:
+The `scda.test` package has several dependencies required to run the tests within this package. Before installing the `scda.test` repository, please ensure you have the latest versions of the `tern` and `random.cdisc.data` packages installed. Installation instructions are provided for each at these links:
 
 - [`tern`](https://github.com/insightsengineering/tern#installation)
-- [`scda`](https://github.com/insightsengineering/scda#installation)
-- [`scda.2022`](https://github.com/insightsengineering/scda.2022#installation)
+- [`random.cdisc.data`](https://github.com/insightsengineering/random.cdisc.data#installation)
 
 ### Installing scda.test
 

staged_dependencies.yaml

@@ -10,11 +10,8 @@ upstream_repos:
   insightsengineering/rtables:
     repo: insightsengineering/rtables
     host: https://github.com
-  insightsengineering/scda:
-    repo: insightsengineering/scda
-    host: https://github.com
-  insightsengineering/scda.2022:
-    repo: insightsengineering/scda.2022
+  insightsengineering/random.cdisc.data:
+    repo: insightsengineering/random.cdisc.data
     host: https://github.com
   insightsengineering/tern:
     repo: insightsengineering/tern

tests/testthat/setup.R

@@ -1,29 +1,28 @@
 # Extra libraries (suggested) for tests
 library(dplyr)
-library(scda.2022)
 library(tern)
 library(lubridate)
 
 # Data loading for tests
-adsl_raw <- scda::synthetic_cdisc_dataset("latest", "adsl")
-adab_raw <- scda::synthetic_cdisc_dataset("latest", "adab")
-adae_raw <- scda::synthetic_cdisc_dataset("latest", "adae")
-adaette_raw <- scda::synthetic_cdisc_dataset("latest", "adaette")
-adcm_raw <- scda::synthetic_cdisc_dataset("latest", "adcm")
-addv_raw <- scda::synthetic_cdisc_dataset("latest", "addv")
-adeg_raw <- scda::synthetic_cdisc_dataset("latest", "adeg")
-adex_raw <- scda::synthetic_cdisc_dataset("latest", "adex")
-adhy_raw <- scda::synthetic_cdisc_dataset("latest", "adhy")
-adlb_raw <- scda::synthetic_cdisc_dataset("latest", "adlb")
-admh_raw <- scda::synthetic_cdisc_dataset("latest", "admh")
-adpc_raw <- scda::synthetic_cdisc_dataset("latest", "adpc")
-adpp_raw <- scda::synthetic_cdisc_dataset("latest", "adpp")
-adpc_raw <- scda::synthetic_cdisc_dataset("latest", "adpc")
-adqs_raw <- scda::synthetic_cdisc_dataset("latest", "adqs")
-adrs_raw <- scda::synthetic_cdisc_dataset("latest", "adrs")
-adsub_raw <- scda::synthetic_cdisc_dataset("latest", "adsub")
-adtte_raw <- scda::synthetic_cdisc_dataset("latest", "adtte")
-advs_raw <- scda::synthetic_cdisc_dataset("latest", "advs")
+adsl_raw <- random.cdisc.data::cadsl
+adab_raw <- random.cdisc.data::cadab
+adae_raw <- random.cdisc.data::cadae
+adaette_raw <- random.cdisc.data::cadaette
+adcm_raw <- random.cdisc.data::cadcm
+addv_raw <- random.cdisc.data::caddv
+adeg_raw <- random.cdisc.data::cadeg
+adex_raw <- random.cdisc.data::cadex
+adhy_raw <- random.cdisc.data::cadhy
+adlb_raw <- random.cdisc.data::cadlb
+admh_raw <- random.cdisc.data::cadmh
+adpc_raw <- random.cdisc.data::cadpc
+adpp_raw <- random.cdisc.data::cadpp
+adpc_raw <- random.cdisc.data::cadpc
+adqs_raw <- random.cdisc.data::cadqs
+adrs_raw <- random.cdisc.data::cadrs
+adsub_raw <- random.cdisc.data::cadsub
+adtte_raw <- random.cdisc.data::cadtte
+advs_raw <- random.cdisc.data::cadvs
 
 # skip_if_too_deep
 skip_if_too_deep <- function(depth) { # nolintr

tests/testthat/test-table_aet01_aesi.R

@@ -182,8 +182,8 @@ testthat::test_that("AET01_AESI Variant 2 works as expected", {
 })
 
 testthat::test_that("AET01_AESI Variant 3 works as expected", {
-  adsl <- synthetic_cdisc_dataset("latest", "adsl")
-  adae_mult <- synthetic_cdisc_dataset("latest", "adae")
+  adsl <- adsl_raw
+  adae_mult <- adae_raw
 
   adsl <- filter(adsl, SAFFL == "Y")
   adae_mult <- filter(adae_mult, ANL01FL == "Y" & SAFFL == "Y")

tests/testthat/test-table_dmt01.R

@@ -1,8 +1,13 @@
 # Tests DMT01
+set.seed(1)
 
-adsl <- adsl_raw
-advs <- advs_raw
+# adsl <- adsl_raw
+adsl <- pharmaverseadam::adsl
+adsl <- adsl %>%
+  mutate(BMRKR1 = rnorm(nrow(adsl), 3.5, 10))
+advs <- pharmaverseadam::advs
 adsub <- adsub_raw
+# adsub <- pharmaverseadam::adsub # ??
 
 adsl <- df_explicit_na(adsl)
 advs <- df_explicit_na(advs)
@@ -118,7 +123,7 @@ testthat::test_that("DMT01 variant 3 is produced correctly", {
       vars = c("AGE", "SEX", "RACE"),
       var_labels = c("Age", "Sex", "Race")
     ) %>%
-    split_rows_by("STRATA1",
+    split_rows_by("ACTARMCD",
       split_fun = split_fun
     ) %>%
     analyze_vars("BMRKR1") %>%