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fix as cran #177

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Sep 16, 2022
Merged

fix as cran #177

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45557fb
fix as cran
Sep 9, 2022
4a0ba0f
lintr
Sep 9, 2022
14f83d1
tm_g_ae_oview
mhallal1 Sep 16, 2022
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2 changes: 0 additions & 2 deletions DESCRIPTION
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Expand Up @@ -46,8 +46,6 @@ Suggests:
scda.2021 (>= 0.1.3),
teal.data (>= 0.1.1),
testthat (>= 2.0)
VignetteBuilder:
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#146 (comment) --as-cran complains there are no vignettes but vignettebuilder is specified

knitr
Remotes:
insightsengineering/osprey@*release,
insightsengineering/scda.2021@*release,
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5 changes: 3 additions & 2 deletions R/tm_g_ae_oview.R
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Expand Up @@ -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) {
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28 changes: 15 additions & 13 deletions R/tm_g_heat_bygrade.R
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Expand Up @@ -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 %>%
Expand Down Expand Up @@ -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') %>%
Expand Down Expand Up @@ -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(
Expand All @@ -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"))
Expand Down Expand Up @@ -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),
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22 changes: 12 additions & 10 deletions R/tm_g_patient_profile.R
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Expand Up @@ -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)
Expand All @@ -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)
Expand Down Expand Up @@ -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(
Expand Down Expand Up @@ -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
)
Expand Down Expand Up @@ -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
Expand Down Expand Up @@ -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)]
})
)
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4 changes: 2 additions & 2 deletions README.md
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@@ -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
Expand All @@ -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

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5 changes: 3 additions & 2 deletions man/tm_g_ae_oview.Rd
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18 changes: 10 additions & 8 deletions man/tm_g_heat_bygrade.Rd
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16 changes: 9 additions & 7 deletions man/tm_g_patient_profile.Rd
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