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

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
 
@@ -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)
  }
-
-

R/helper_functions.R

@@ -1,7 +1,7 @@
 # Helper functions
 
 #' prepareData
-#' 
+#'
 #' Create data.table with input data for testing purposes
 #'
 #' @param cell_lines data.table with cell line info
@@ -10,11 +10,11 @@
 #' @keywords generate_test_data
 #'
 #' @return data.table with input data for testing
-#' 
+#'
 #' @examples
-#' 
+#'
 #' prepareData(create_synthetic_cell_lines(), create_synthetic_drugs())
-#' 
+#'
 #' @export
 prepareData <- function(cell_lines, drugs, conc = 10 ^ (seq(-3, 1, 0.5))) {
   df_layout <- data.table::as.data.table(merge.data.frame(cell_lines, drugs, by = NULL))
@@ -23,29 +23,29 @@ prepareData <- function(cell_lines, drugs, conc = 10 ^ (seq(-3, 1, 0.5))) {
 }
 
 #' prepareMergedData
-#' 
-#' Create data.table with input data containing noise for testing purposes 
+#'
+#' Create data.table with input data containing noise for testing purposes
 #'
 #' @param cell_lines data.table with cell line info
 #' @param drugs data.table with drug info
 #' @param noise number indicating level of noise
 #' @keywords generate_test_data
 #'
 #' @return data.table with input data for testing
-#' 
+#'
 #' @examples
-#' 
+#'
 #' prepareMergedData(create_synthetic_cell_lines(), create_synthetic_drugs())
-#' 
+#'
 #' @export
 prepareMergedData <- function(cell_lines, drugs, noise = 0.1) {
   df <- prepareData(cell_lines, drugs)
   generate_response_data(df, noise)
 }
 
 #' prepareComboMergedData
-#' 
-#' Create data.table with input combination data containing noise for testing purposes 
+#'
+#' Create data.table with input combination data containing noise for testing purposes
 #'
 #' @param cell_lines data.table with cell line info
 #' @param drugs data.table with drug info
@@ -58,68 +58,68 @@ prepareMergedData <- function(cell_lines, drugs, noise = 0.1) {
 #' @keywords generate_test_data
 #'
 #' @return data.table with input data for testing
-#' 
+#'
 #' @examples
-#' 
+#'
 #' prepareComboMergedData(create_synthetic_cell_lines(), create_synthetic_drugs())
-#' 
+#'
 #' @export
-prepareComboMergedData <- function(cell_lines, 
-                                   drugs, 
+prepareComboMergedData <- function(cell_lines,
+                                   drugs,
                                    drugsIdx1 = 2:4,
-                                   drugsIdx2 = c(26, 26, 26), 
-                                   concentration = c(0, .2, 1), 
-                                   noise = 0.1, 
+                                   drugsIdx2 = c(26, 26, 26),
+                                   concentration = c(0, .2, 1),
+                                   noise = 0.1,
                                    modifyDf2 = FALSE) {
   df_layout <- prepareData(cell_lines, drugs[drugsIdx1, ])
-  
+
   df_2 <- cbind(drugs[drugsIdx2, ], Concentration = concentration)
   colnames(df_2) <- paste0(colnames(df_2), "_2")
-  
+
   df_layout_2 <- data.table::as.data.table(merge.data.frame(df_layout, df_2, by = NULL))
   if (modifyDf2) {
     df_layout_2 <- df_layout_2[!(df_layout_2$Concentration == 0 & df_layout_2$Concentration_2 > 0), ]
   }
-  
+
   generate_response_data(df_layout_2, noise)
 }
 
 #' prepareCodilutionData
-#' 
-#' Create data.table with input co-dilution data containing noise for testing purposes 
+#'
+#' Create data.table with input co-dilution data containing noise for testing purposes
 #'
 #' @param cell_lines data.table with cell line info
 #' @param drugs data.table with drug info
 #' @param drugsIdx2 numeric vector of ids for secondary drug (in `drugs` data.table)
 #' @param conc vector of doses
 #' @param noise number indicating level of noise
 #' @keywords generate_test_data
-#' 
+#'
 #' @return data.table with input data for testing
-#' 
+#'
 #' @examples
-#' 
+#'
 #' prepareCodilutionData(create_synthetic_cell_lines()[seq_len(2), ],
 #'                       create_synthetic_drugs()[seq_len(4), ])
-#' 
+#'
 #' @export
 prepareCodilutionData <- function(cell_lines,
                                   drugs,
                                   drugsIdx2 = 1,
                                   conc = 10 ^ (seq(-3, 1, 0.5)),
                                   noise = 0.1) {
-  
+
   df_layout <- prepareData(cell_lines = cell_lines, drugs = drugs, conc = conc)
-  
+
   df_2 <- cbind(drugs[drugsIdx2, , drop = FALSE],
                 df_layout[, "Concentration", drop = FALSE])
   colnames(df_2) <- paste0(colnames(df_2), "_2")
-  
+
   df_layout_2 <- cbind(df_layout, df_2)
   df_layout_2 <- df_layout_2[df_layout_2$DrugName != df_layout_2$DrugName_2, ]
   rows <- which(df_layout_2$Concentration_2 > 0)
   cols <- c("Concentration", "Concentration_2")
   df_layout_2[rows, (cols) := lapply(.SD, function(x) x / 2), .SDcols = cols]
-  
+
   generate_response_data(df_layout_2, noise)
 }

R/package.R

@@ -6,7 +6,7 @@
 #' @examples
 #' path <- system.file("annotation_data", "cell_lines.csv", package = "gDRtestData")
 #' data.table::fread(file = path)
-#' 
+#'
 #' @return data.table
 NULL
 
@@ -15,9 +15,9 @@ NULL
 #' @name drugs
 #' @docType data
 #' @keywords data internal
-#' @examples 
+#' @examples
 #' path <- system.file("annotation_data", "drugs.csv", package = "gDRtestData")
 #' data.table::fread(file = path)
-#' 
+#'
 #' @return data.table
 NULL