fix: resolve gDRstyle linting violations

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: gDRtestData
 Title: gDRtestData - R data package with testing dose response data
-Version: 1.11.1
+Version: 1.11.2
 Date: 2026-04-29
 Description: R package with internal dose-response test data. Package provides functions to generate
   input testing data that can be used as the input for gDR pipeline. It also contains qs2 files
@@ -41,5 +41,5 @@ VignetteBuilder: knitr
 License: Artistic-2.0
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE) 
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.3
 Config/testthat/edition: 3

NEWS.md

@@ -1,3 +1,6 @@
+## gDRtestData 1.11.2 - 2026-05-18
+* apply updated gDRstyle rules
+
 ## gDRtestData 1.11.1 - 2026-04-29
 * synchronize Bioconductor and GitHub versioning
 
@@ -76,10 +79,10 @@
 * update testdata
 
 ## gDRtestData 0.99.19 - 2023-06-23
-* BiocStyle added to dependency
+* add BiocStyle to dependency
 
 ## gDRtestData 0.99.18 - 2023-06-22
-* replaced rds files with qs
+* replace rds files with qs
 
 ## gDRtestData 0.99.17 - 2023-06-15
 * switch from merge to [[
@@ -90,7 +93,7 @@
 ## gDRtestData 0.99.15 - 2023-05-24
 * format the vignette with BiocStyle
 
-## gDRtestData 0.99.14 - 22023-05-15
+## gDRtestData 0.99.14 - 2023-05-15
 * fix related with data.table
 
 ## gDRtestData 0.99.13 - 2023-05-15
@@ -100,10 +103,10 @@
 * update testdata as per new data model
 
 ## gDRtestData 0.99.11 - 2023-04-25
-* changed data.frame to data.table
+* change data.frame to data.table
 
 ## gDRtestData 0.99.10 - 2023-04-24
-* removing redundant files
+* remove redundant files
 
 ## gDRtestData 0.99.9 - 2023-04-20
 * fix warning in Bioc check
@@ -135,4 +138,4 @@
 ## gDRtestData 0.99.0 - 2023-03-31
 * preparing package for Bioc submission
 * fix examples
-
+

R/generate_data.R

@@ -7,17 +7,17 @@
 #'
 #'
 #' @examples
-#' 
+#'
 #' cell_lines <- create_synthetic_cell_lines()
 #' add_data_replicates(cell_lines)
-#' 
+#'
 #' @return data.table with replicates
 #' @keywords generate_data
 #' @export
 #'
 add_data_replicates <- function(df_layout) {
   df_layout_duplicates <- Reduce(rbind, list(df_layout)[rep(1, times = 3)])
-  barcode <- do.call(c, lapply(paste0("plate_", seq_len(3)), function(x) rep(x, nrow(df_layout))))
+  barcode <- do.call(c, lapply(paste0("plate_", seq_len(3)), function(x) rep(x, NROW(df_layout))))
   cbind(Barcode = barcode, df_layout_duplicates)
 }
 
@@ -30,10 +30,10 @@ add_data_replicates <- function(df_layout) {
 #' @keywords generate_data
 #'
 #' @examples
-#' 
+#'
 #' cell_lines <- create_synthetic_cell_lines()
 #' add_concentration(cell_lines)
-#' 
+#'
 #' @return data.table with concentrations
 #' @export
 #'
@@ -55,41 +55,41 @@ add_concentration <- function(df_layout, concentrations = 10 ^ (seq(-3, 1, 0.5))
 #'
 #'
 #' @examples
-#' 
+#'
 #' cell_lines <- create_synthetic_cell_lines()
 #' drugs <- create_synthetic_drugs()
 #' df_layout <- prepareData(cell_lines[seq_len(2), ], drugs[seq_len(4), ])
 #' generate_response_data(df_layout)
-#' 
+#'
 #'
 #' @return data.table with response data
 #' @export
 #'
 generate_response_data <- function(df_layout, noise_level = 0.1) {
-  
+
   drugs <- create_synthetic_drugs()
   cell_lines <- create_synthetic_cell_lines()
   hill_coef <- generate_hill_coef(drugs, cell_lines)
   ec50 <- generate_ec50(drugs, cell_lines)
   e_inf <- generate_e_inf(drugs, cell_lines)
-  
+
   df_layout$ReadoutValue <- round(100 * pmax(
     getReadoutCoef(df_layout, e_inf, ec50, hill_coef) +
-      (noise_level * stats::runif(nrow(df_layout)) - (noise_level / 2)),  # add some noise
-    0.01 * stats::runif(nrow(df_layout)) + 0.005), # avoid hard 0 values
+      (noise_level * stats::runif(NROW(df_layout)) - (noise_level / 2)),  # add some noise
+    0.01 * stats::runif(NROW(df_layout)) + 0.005), # avoid hard 0 values
     1)
   df_layout$BackgroundValue <- 0
   df_layout$Duration <- 72
   df_layout <- introduceVehicle(df_layout)
-  
+
   if ("Gnumber_2" %in% colnames(df_layout)) { # combo data
     df_layout <- introduceGNum(df_layout, e_inf, ec50, hill_coef, "_2")
   }
-  
+
   if ("Gnumber_3" %in% colnames(df_layout)) { # combo data
     df_layout <- introduceGNum(df_layout, e_inf, ec50, hill_coef, "_3")
   }
-  
+
   df_layout
 }
 
@@ -98,32 +98,32 @@ getReadoutCoef <- function(df, e_inf, ec50, hill_coef, suffix = "") {
   apply(df, 1, function(x) {
     clid <- x["clid"]
     gnum <- x[paste0("Gnumber", suffix)]
-    
+
     e_inf_val <- e_inf[gnum, clid]
     ec50_val <- ec50[gnum, clid]
     hill_val <- hill_coef[gnum, clid]
     concentration <- as.numeric(x["Concentration"])
-    
-    e_inf_val + (1 - e_inf_val) * (ec50_val ^ hill_val / (concentration ^ hill_val + ec50_val ^ hill_val)) 
+
+    e_inf_val + (1 - e_inf_val) * (ec50_val ^ hill_val / (concentration ^ hill_val + ec50_val ^ hill_val))
   })
 }
 
 #' @keywords internal
 introduceVehicle <- function(df, suffix = "") {
   zeroIdx <- df[[paste0("Concentration", suffix)]] == 0
-  
+
   df[zeroIdx, paste0("Gnumber", suffix)] <- "vehicle"
   df[zeroIdx, paste0("DrugName", suffix)] <- "vehicle"
   df[zeroIdx, paste0("drug_moa", suffix)] <- "vehicle"
-  
+
   df
 }
 
 #' @keywords internal
 introduceGNum <- function(df, e_inf, ec50, hill_coef, suffix) {
   df$ReadoutValue <- df$ReadoutValue * getReadoutCoef(df, e_inf, ec50, hill_coef, suffix)
   df <- introduceVehicle(df, suffix)
-  
+
   df
 }
 
@@ -134,7 +134,7 @@ introduceGNum <- function(df, e_inf, ec50, hill_coef, suffix) {
 #' @keywords generate_data
 #'
 #' @examples
-#' 
+#'
 #' cell_lines <- create_synthetic_cell_lines()
 #' drugs <- create_synthetic_drugs()
 #' df_merged <- prepareData(cell_lines[seq_len(2), ], drugs[seq_len(4), ])
@@ -152,14 +152,14 @@ add_day0_data <- function(df_merged, noise_level = 0.05) {
     TRUE
   }
   df_Day0 <- unique(df_merged[df_merged$Concentration == 0 & cond, ])
-  
+
   df_Day0$ReadoutValue <- df_Day0$ReadoutValue / 2 ^ (df_Day0$Duration / df_Day0$ReferenceDivisionTime)
-  coef <- (1 - noise_level / 2 + noise_level * stats::runif(nrow(df_Day0)))
+  coef <- (1 - noise_level / 2 + noise_level * stats::runif(NROW(df_Day0)))
   df_Day0$ReadoutValue <- round(df_Day0$ReadoutValue * coef, 1)
-  
+
   df_Day0$Duration <- 0
   df_Day0$Barcode <- "plate_0"
-  
+
   df_merged <- rbind(df_merged, df_Day0)
   df_merged
 }

R/get_test_datasets.R

@@ -1,5 +1,5 @@
 #' get_test_dataset_paths
-#' 
+#'
 #' Returns named vector of absolute paths to test datasets.
 #'
 #' @param datasets_dir path to directory with datasets (default \code{NULL}).
@@ -9,13 +9,13 @@
 #' @keywords generate_test_data
 #'
 #' @return named vector of absolute paths
-#' 
+#'
 #' @examples
-#' 
+#'
 #' get_test_dataset_paths()
 #' path <- system.file("testdata", package = "gDRtestData", mustWork = TRUE)
 #' get_test_dataset_paths(path)
-#' 
+#'
 #' @export
 #'
 #' @author Kamil Foltyński \email{kamil.foltynski@@contractors.roche.com}
@@ -30,12 +30,10 @@ get_test_dataset_paths <-
    }
    checkmate::assert_string(datasets_dir, min.chars = 1)
    checkmate::assert_directory_exists(datasets_dir)
-   
+
    checkmate::assert_string(pattern, min.chars = 1)
-   
+
    epaths <- list.files(datasets_dir, pattern = paste0(pattern, ".*\\.qs2$"), full.names = TRUE)
    enames <- gsub(pattern, "", gsub("\\.qs2$", "", basename(epaths)))
    structure(epaths, names = enames)
  }
-
-