Decouple scda

.github/workflows/check.yaml

@@ -34,7 +34,7 @@ jobs:
     with:
       additional-env-vars: |
         _R_CHECK_CRAN_INCOMING_REMOTE_=false
-        _R_CHECK_EXAMPLE_TIMING_THRESHOLD_=10
+        _R_CHECK_EXAMPLE_TIMING_THRESHOLD_=5
       additional-r-cmd-check-params: --as-cran
       enforce-note-blocklist: true
       note-blocklist: |

DESCRIPTION

@@ -32,7 +32,7 @@ Imports:
     lifecycle,
     logger (>= 0.2.0),
     shinyvalidate,
-    teal.code (>= 0.2.0),
+    teal.code (>= 0.3.0),
     teal.logger (>= 0.1.1),
     teal.reporter (>= 0.1.1),
     teal.transform (>= 0.3.0),
@@ -43,15 +43,11 @@ Suggests:
     knitr,
     nestcolor (>= 0.1.0),
     rmarkdown,
-    scda (>= 0.1.5),
-    scda.2022 (>= 0.1.3),
     teal.data (>= 0.1.2),
     testthat (>= 2.0)
 Remotes:
     insightsengineering/osprey@*release,
     insightsengineering/osprey@*release,
-    insightsengineering/scda.2022@*release,
-    insightsengineering/scda@*release,
     insightsengineering/teal.code@*release,
     insightsengineering/teal.data@*release,
     insightsengineering/teal.logger@*release,

NEWS.md

@@ -1,6 +1,6 @@
 # teal.osprey 0.1.15.9013
 
-* Examples now use `scda.2022` instead of `scda.2021`.
+* Removed `scda` package dependency from examples.
 * Fixed crash in `tm_g_heat_bygrade` when not plotting `Conmed`. 
 * Added validation to `tm_g_spiderplot.R` that checks if there are duplicates in X and Y facet variables.
 * Improved input validation and used the `teal::validate_inputs` mechanism to send validation messages to the output panel.
@@ -10,7 +10,7 @@
 ### Breaking changes
 
 * Replaced `chunks` with simpler `qenv` class.
-* Replaced `datasets` argument containing `FilteredData` with the new arguments `data` (`tdata` object) and `filter_panel_api` (`FilterPanelAPI`).
+* In all `tm_xyz_srv` modules `datasets` argument containing `FilteredData` have been replaced with the new argument `data` (`tdata` object) and `filter_panel_api` (`FilterPanelAPI`).
 * Updated `arm_var` to point to the factor column in `ANL`. It can't be a character column anymore.
 * Removed redundant formal arguments from `tm_g_patient_profile`.
 
@@ -21,7 +21,7 @@
 
 ### Enhancements
 * Added `teal.reporter` to all modules.
 * Updated `shiny::validate` calls to `shinyvalidate` for better `UI` overview.
 * Implemented `nestcolor` with slight refactoring to `tm_g_swimlane`. Added `nestcolor` in examples.
 
 ### Miscellaneous
@@ -44,7 +44,7 @@
 * The label of the select input widget to choose the `paramcd` is no longer hard coded to `ADTR` in `tm_g_spiderplot`.
 
 ### Miscellaneous
 * Rewrote module to use `moduleServer` and updated calls to `teal.devel` modules which have also been written to use `moduleServer`.
 * Replaced calls to `teal::root_modules` with `teal::modules` following deprecation of `teal::root_modules`.
 * Adjusted package imports to take into account changes to the `teal` framework.
 * Functions from imported packages are now fully specified.
@@ -62,7 +62,7 @@
 * Fixed a bug in `tm_g_waterfall` so that the `Tumor Burden Parameter` `UI` element is now respected.
 
 ### Miscellaneous
 * Updated R version requirement to `R >= 3.6`.
 * Removed the function `teal::keys` in the examples of `tm_g_spiderplot` and `tm_g_waterfall` modules.
 * Removed dependency on `test.nest` package.
 * Removed dependency on `utils.nest` package and replaced its functions with equivalents from the `checkmate` package.
@@ -79,14 +79,14 @@
 # teal.osprey 0.1.10
 
 ### Enhancements
 * Added a Shiny feature to `tm_g_swimlane` that will prevent needless re-render of the output when the user has not completely provided inputs to the vertical lines widget.
 
 ### Miscellaneous
 * Altered the `Choose Up To 2:` inputs widget from the Encoding Panel to be independent of the Filtering Panel in `tm_g_butterfly`.
 * Updated warning message when Tumor Burden Parameter is not selected in `tm_g_waterfall`.
 
 ### Bug fixes
 * Fixed a bug in `tm_g_butterfly` that displays the filtering and faceting widgets despite not being provided in the arguments.
 
 # teal.osprey 0.1.9
 
@@ -95,8 +95,8 @@
 * Added new `teal` module `tm_g_ae_sub` for an `AE` by subgroups plot.
 
 ### Bug fixes
 * Fixed misleading validate message in `tm_g_ae_oview` when either Control or Treatment variable is filtered out.
 * Added a validate statement to output a better error message when both the left and right dichotomization values are filtered out of data.
 
 ### Miscellaneous
 * Improved reactivity dependencies across modules.
@@ -104,33 +104,33 @@
 # teal.osprey 0.1.8
 
 * Added validation message if the dataset does not contain subjects from both the control and treatment arms in `tm_g_events_term_id`.
 * Improved validation message if subject has been filtered out of dataset when used with `tm_g_patient_profile`.
 * Fixed modules due to changes to `plot_with_settings` in latest `teal.devel` release.
 * Updated study day and duration derivation in `tm_g_patient_profile`.
 
 # teal.osprey 0.1.7
 
 ### Enhancements
 * Added additional validation for horizontal and vertical reference lines in `tm_g_spider_plot`.
 
 ### Bug Fixes
 * Fixed `tm_g_patient_profile` when adverse event line color variable is not selected.
 * Fixed the issue of unknown date format and established minimum number of observation threshold in `tm_g_patient_profile`.
 
 ### Miscellaneous
 * Retired the following `teal` modules due to duplication in `teal.modules.clinical`:
   - Teal module for `AE` overview summary table - can be replaced with `teal.modules.clinical::tm_t_events_summary`.
   - Teal module for `AE` summary table by preferred terms - can be replaced with `teal.modules.clinical::tm_t_events`.
   - Teal module for `AE` summary table by highest `NCI-CTCAE` grade - can be replaced with `teal.modules.clinical::tm_t_events_by_grade`.
   - Teal module for Disposition table - can be replaced with `teal.modules.clinical::tm_t_summary`.
 * Moved `code` argument to `cdisc_dataset` (from `cdisc_data`) in examples.
 
 # teal.osprey 0.1.6
 
 * All graph modules now accept a `plot_width` argument which specifies the plot width and renders a slider to adjust the width interactively in the module.
 * Replaced `plot_with_height` with `plot_with_settings` module throughout package.
 * Show R Code now produces code generating only the datasets needed for the current module, not all datasets included in the data argument of `teal::init`.
 * Evaluate chunks with `chunks_safe_eval` rather than `chunks_eval`.
 
 # teal.osprey 0.1.5
 

R/tm_g_ae_oview.R

@@ -16,12 +16,10 @@
 #' @export
 #'
 #' @examples
-#' library(scda)
 #' library(nestcolor)
 #'
-#' latest_data <- synthetic_cdisc_data("latest")
-#' ADSL <- latest_data$adsl
-#' ADAE <- latest_data$adae
+#' ADSL <- osprey::rADSL
+#' ADAE <- osprey::rADAE
 #'
 #' # Add additional dummy causality flags.
 #' add_event_flags <- function(dat) {
@@ -47,10 +45,10 @@
 #'
 #' app <- init(
 #'   data = cdisc_data(
-#'     cdisc_dataset("ADSL", ADSL, code = "ADSL <- synthetic_cdisc_data(\"latest\")$adsl"),
+#'     cdisc_dataset("ADSL", ADSL, code = "ADSL <- osprey::rADSL"),
 #'     cdisc_dataset("ADAE", ADAE,
 #'       code =
-#'         "ADAE <- synthetic_cdisc_data('latest')$adae
+#'         "ADAE <- osprey::rADAE
 #'            add_event_flags <- function(dat) {
 #'              dat <- dat %>%
 #'                dplyr::mutate(

R/tm_g_ae_sub.R

@@ -18,15 +18,13 @@
 #'
 #' @examples
 #' # Example using stream (ADaM) dataset
-#' library(scda)
-#'
-#' ADSL <- synthetic_cdisc_data("latest")$adsl
-#' ADAE <- synthetic_cdisc_data("latest")$adae
+#' ADSL <- osprey::rADSL
+#' ADAE <- osprey::rADAE
 #'
 #' app <- init(
 #'   data = cdisc_data(
-#'     cdisc_dataset("ADSL", ADSL, code = "ADSL <- synthetic_cdisc_data(\"latest\")$adsl"),
-#'     cdisc_dataset("ADAE", ADAE, code = "ADAE <- synthetic_cdisc_data(\"latest\")$adae"),
+#'     cdisc_dataset("ADSL", ADSL, code = "ADSL <- osprey::rADSL"),
+#'     cdisc_dataset("ADAE", ADAE, code = "ADAE <- osprey::rADAE"),
 #'     check = TRUE
 #'   ),
 #'   modules = modules(

R/tm_g_butterfly.R

@@ -43,12 +43,11 @@
 #'
 #' # Example using stream (ADaM) dataset
 #' library(dplyr)
-#' library(scda)
 #' library(nestcolor)
 #'
 #' set.seed(23)
-#' ADSL <- synthetic_cdisc_data("latest")$adsl
-#' ADAE <- synthetic_cdisc_data("latest")$adae
+#' ADSL <- osprey::rADSL
+#' ADAE <- osprey::rADAE
 #' ADSL <- mutate(ADSL, DOSE = paste(sample(1:3, n(), replace = TRUE), "UG"))
 #' ADAE <- mutate(
 #'   ADAE,
@@ -61,12 +60,12 @@
 #' app <- init(
 #'   data = cdisc_data(
 #'     cdisc_dataset("ADSL", ADSL,
-#'       code = "ADSL <- synthetic_cdisc_data(\"latest\")$adsl
+#'       code = "ADSL <- osprey::rADSL
 #'               set.seed(23)
 #'               ADSL <- mutate(ADSL, DOSE = paste(sample(1:3, n(), replace = TRUE), 'UG'))"
 #'     ),
 #'     cdisc_dataset("ADAE", ADAE,
-#'       code = "ADAE <- synthetic_cdisc_data(\"latest\")$adae
+#'       code = "ADAE <- osprey::rADAE
 #'               ADAE <- mutate(ADAE,
 #'               flag1 = ifelse(AETOXGR == 1, 1, 0),
 #'               flag2 = ifelse(AETOXGR == 2, 1, 0),

R/tm_g_events_term_id.R

@@ -18,16 +18,15 @@
 #' @author Molly He (hey59) \email{hey59@gene.com}
 #'
 #' @examples
-#' library(scda)
 #' library(nestcolor)
 #'
-#' ADSL <- synthetic_cdisc_data("latest")$adsl
-#' ADAE <- synthetic_cdisc_data("latest")$adae
+#' ADSL <- osprey::rADSL
+#' ADAE <- osprey::rADAE
 #'
 #' app <- init(
 #'   data = cdisc_data(
-#'     cdisc_dataset("ADSL", ADSL, code = "ADSL <- synthetic_cdisc_data(\"latest\")$adsl"),
-#'     cdisc_dataset("ADAE", ADAE, code = "ADAE <- synthetic_cdisc_data(\"latest\")$adae"),
+#'     cdisc_dataset("ADSL", ADSL, code = "ADSL <- osprey::rADSL"),
+#'     cdisc_dataset("ADAE", ADAE, code = "ADAE <- osprey::rADAE"),
 #'     check = TRUE
 #'   ),
 #'   modules = modules(

R/tm_g_heat_bygrade.R

@@ -34,14 +34,12 @@
 #' @export
 #'
 #' @examples
-#' library(scda)
 #' library(dplyr)
 #' library(nestcolor)
-#' 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$USUBJID)
+#' ADSL <- osprey::rADSL %>% slice(1:30)
+#' ADEX <- osprey::rADEX %>% filter(USUBJID %in% ADSL$USUBJID)
+#' ADAE <- osprey::rADAE %>% filter(USUBJID %in% ADSL$USUBJID)
+#' ADCM <- osprey::rADCM %>% filter(USUBJID %in% ADSL$USUBJID)
 #'
 #' # This preprocess is only to force legacy standard on ADCM
 #' ADCM <- ADCM %>%
@@ -80,11 +78,10 @@
 #'     cdisc_dataset("ADAE", ADAE),
 #'     cdisc_dataset("ADCM", ADCM, keys = c("STUDYID", "USUBJID", "ASTDTM", "CMSEQ", "CMDECOD")),
 #'     code = "
-#'     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$USUBJID)
+#'     ADSL <- osprey::rADSL %>% slice(1:30)
+#'     ADEX <- osprey::rADEX %>% filter(USUBJID %in% ADSL$USUBJID)
+#'     ADAE <- osprey::rADAE %>% filter(USUBJID %in% ADSL$USUBJID)
+#'     ADCM <- osprey::rADCM %>% filter(USUBJID %in% ADSL$USUBJID)
 #'     ADCM <- ADCM %>% select(-starts_with(\"ATC\")) %>% unique()
 #'     ADEX  <- ADEX %>%
 #'       filter(PARCAT1 == 'INDIVIDUAL') %>%

R/tm_g_patient_profile.R

@@ -62,18 +62,15 @@
 #' @export
 #'
 #' @examples
-#' library(scda)
 #' library(nestcolor)
 #'
-#' latest_data <- synthetic_cdisc_data("latest")
-#'
-#' ADSL <- latest_data$adsl
-#' ADAE <- latest_data$adae %>%
+#' ADSL <- osprey::rADSL
+#' ADAE <- osprey::rADAE %>%
 #'   mutate(
 #'     ASTDT = as.Date(ASTDTM),
 #'     AENDT = as.Date(AENDTM)
 #'   )
-#' ADCM <- latest_data$adcm %>%
+#' ADCM <- osprey::rADCM %>%
 #'   mutate(
 #'     ASTDT = as.Date(ASTDTM),
 #'     AENDT = as.Date(AENDTM)
@@ -84,47 +81,42 @@
 #'   select(-starts_with("ATC")) %>%
 #'   unique()
 #'
-#' ADRS <- latest_data$adrs %>%
+#' ADRS <- osprey::rADRS %>%
 #'   mutate(ADT = as.Date(ADTM))
-#' ADEX <- latest_data$adex %>%
+#' ADEX <- osprey::rADEX %>%
 #'   mutate(
 #'     ASTDT = as.Date(ASTDTM),
 #'     AENDT = as.Date(AENDTM)
 #'   )
-#' ADLB <- latest_data$adlb %>%
+#' ADLB <- osprey::rADLB %>%
 #'   mutate(
 #'     ADT = as.Date(ADTM),
 #'     LBSTRESN = as.numeric(LBSTRESC)
 #'   )
 #'
 #' app <- init(
 #'   data = cdisc_data(
-#'     cdisc_dataset("ADSL", ADSL,
-#'       code = "ADSL <- synthetic_cdisc_data(\"latest\")$adsl"
-#'     ),
-#'     cdisc_dataset("ADRS", ADRS,
-#'       code = "ADRS <- synthetic_cdisc_data(\"latest\")$adrs %>%
-#'               mutate(ADT = as.Date(ADTM))"
-#'     ),
+#'     cdisc_dataset("ADSL", ADSL, code = "ADSL <- osprey::rADSL"),
+#'     cdisc_dataset("ADRS", ADRS, code = "ADRS <- osprey::rADRS %>% mutate(ADT = as.Date(ADTM))"),
 #'     cdisc_dataset("ADAE", ADAE,
-#'       code = "ADAE <- synthetic_cdisc_data(\"latest\")$adae %>%
+#'       code = "ADAE <- osprey::rADAE %>%
 #'               mutate(ASTDT = as.Date(ASTDTM),
 #'                      AENDT = as.Date(AENDTM))"
 #'     ),
 #'     cdisc_dataset("ADCM", ADCM,
-#'       code = "ADCM <- synthetic_cdisc_data(\"latest\")$adcm %>%
+#'       code = "ADCM <- osprey::rADCM %>%
 #'               mutate(ASTDT = as.Date(ASTDTM),
 #'                      AENDT = as.Date(AENDTM))
 #'               ADCM <- ADCM %>% select(-starts_with(\"ATC\")) %>% unique()",
 #'       keys = c("STUDYID", "USUBJID", "ASTDTM", "CMSEQ", "CMDECOD")
 #'     ),
 #'     cdisc_dataset("ADLB", ADLB,
-#'       code = "ADLB <- synthetic_cdisc_data(\"latest\")$adlb %>%
+#'       code = "ADLB <- osprey::rADLB %>%
 #'               mutate(ADT = as.Date(ADTM),
 #'                      LBSTRESN = as.numeric(LBSTRESC))"
 #'     ),
 #'     cdisc_dataset("ADEX", ADEX,
-#'       code = "ADEX <- synthetic_cdisc_data(\"latest\")$adex %>%
+#'       code = "ADEX <- osprey::rADEX %>%
 #'               mutate(ASTDT = as.Date(ASTDTM),
 #'                      AENDT = as.Date(AENDTM))"
 #'     ),

R/tm_g_spiderplot.R

@@ -28,17 +28,16 @@
 #'
 #' # Example using stream (ADaM) dataset
 #' library(dplyr)
-#' library(scda)
 #' library(nestcolor)
 #'
-#' ADSL <- synthetic_cdisc_data("latest")$adsl
-#' ADTR <- synthetic_cdisc_data("latest")$adtr
+#' ADSL <- osprey::rADSL
+#' ADTR <- osprey::rADTR
 #'
 #' app <- teal::init(
 #'   data = cdisc_data(
-#'     cdisc_dataset("ADSL", ADSL, code = "ADSL <- synthetic_cdisc_data(\"latest\")$adsl"),
+#'     cdisc_dataset("ADSL", ADSL, code = "ADSL <- osprey::rADSL"),
 #'     cdisc_dataset("ADTR", ADTR,
-#'       code = "ADTR <- synthetic_cdisc_data(\"latest\")$adtr",
+#'       code = "ADTR <- osprey::rADTR",
 #'       keys = c("STUDYID", "USUBJID", "PARAMCD", "AVISIT")
 #'     ),
 #'     check = TRUE

README.md

@@ -22,11 +22,11 @@
 <!-- end badges -->
 
 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
 
 For releases from August 2022 it is recommended that you [create and use a GitHub PAT](https://docs.github.com/en/github/authenticating-to-github/keeping-your-account-and-data-secure/creating-a-personal-access-token) to install the latest version of this package. Once you have the PAT, run the following:
 
 ```r
 Sys.setenv(GITHUB_PAT = "your_access_token_here")
@@ -36,8 +36,6 @@
 
 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.
-
 ## Stargazers and Forkers
 
 ### Stargazers over time